no code implementations • 5 May 2024 • Xin Jin, Qianqian Qiao, Yi Lu, Shan Gao, Heng Huang, Guangdong Li
This dataset solely comprises overall scores for high-quality artistic images.
no code implementations • 24 Apr 2024 • Xin Jin, Tiejun Lv, Wei Ni, Zhipeng Lin, Qiuming Zhu, Ekram Hossain, H. Vincent Poor
Dual-function-radar-communication (DFRC) is a promising candidate technology for next-generation networks.
no code implementations • 22 Apr 2024 • Marah Abdin, Sam Ade Jacobs, Ammar Ahmad Awan, Jyoti Aneja, Ahmed Awadallah, Hany Awadalla, Nguyen Bach, Amit Bahree, Arash Bakhtiari, Harkirat Behl, Alon Benhaim, Misha Bilenko, Johan Bjorck, Sébastien Bubeck, Martin Cai, Caio César Teodoro Mendes, Weizhu Chen, Vishrav Chaudhary, Parul Chopra, Allie Del Giorno, Gustavo de Rosa, Matthew Dixon, Ronen Eldan, Dan Iter, Amit Garg, Abhishek Goswami, Suriya Gunasekar, Emman Haider, Junheng Hao, Russell J. Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahoud Khademi, Lev Kurilenko, James R. Lee, Yin Tat Lee, Yuanzhi Li, Chen Liang, Weishung Liu, Eric Lin, Zeqi Lin, Piyush Madan, Arindam Mitra, Hardik Modi, Anh Nguyen, Brandon Norick, Barun Patra, Daniel Perez-Becker, Thomas Portet, Reid Pryzant, Heyang Qin, Marko Radmilac, Corby Rosset, Sambudha Roy, Olatunji Ruwase, Olli Saarikivi, Amin Saied, Adil Salim, Michael Santacroce, Shital Shah, Ning Shang, Hiteshi Sharma, Xia Song, Masahiro Tanaka, Xin Wang, Rachel Ward, Guanhua Wang, Philipp Witte, Michael Wyatt, Can Xu, Jiahang Xu, Sonali Yadav, Fan Yang, ZiYi Yang, Donghan Yu, Chengruidong Zhang, Cyril Zhang, Jianwen Zhang, Li Lyna Zhang, Yi Zhang, Yue Zhang, Yunan Zhang, Xiren Zhou
We introduce phi-3-mini, a 3. 8 billion parameter language model trained on 3. 3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3. 5 (e. g., phi-3-mini achieves 69% on MMLU and 8. 38 on MT-bench), despite being small enough to be deployed on a phone.
no code implementations • 18 Apr 2024 • Chao Jin, Zili Zhang, Xuanlin Jiang, Fangyue Liu, Xin Liu, Xuanzhe Liu, Xin Jin
We implement RAGCache and evaluate it on vLLM, a state-of-the-art LLM inference system and Faiss, a state-of-the-art vector database.
no code implementations • 15 Apr 2024 • Bingyang Wu, Shengyu Liu, Yinmin Zhong, Peng Sun, Xuanzhe Liu, Xin Jin
The context window of large language models (LLMs) is rapidly increasing, leading to a huge variance in resource usage between different requests as well as between different phases of the same request.
1 code implementation • 25 Mar 2024 • Kecheng Zheng, Yifei Zhang, Wei Wu, Fan Lu, Shuailei Ma, Xin Jin, Wei Chen, Yujun Shen
Motivated by this, we propose to dynamically sample sub-captions from the text label to construct multiple positive pairs, and introduce a grouping loss to match the embeddings of each sub-caption with its corresponding local image patches in a self-supervised manner.
no code implementations • 18 Mar 2024 • Liang Xu, Yizhou Zhou, Yichao Yan, Xin Jin, Wenhan Zhu, Fengyun Rao, Xiaokang Yang, Wenjun Zeng
Humans constantly interact with their surrounding environments.
no code implementations • 11 Mar 2024 • Leo Chen, Benjamin Boardley, Ping Hu, Yiru Wang, Yifan Pu, Xin Jin, Yongqiang Yao, Ruihao Gong, Bo Li, Gao Huang, Xianglong Liu, Zifu Wan, Xinwang Chen, Ning Liu, Ziyi Zhang, Dongping Liu, Ruijie Shan, Zhengping Che, Fachao Zhang, Xiaofeng Mou, Jian Tang, Maxim Chuprov, Ivan Malofeev, Alexander Goncharenko, Andrey Shcherbin, Arseny Yanchenko, Sergey Alyamkin, Xiao Hu, George K. Thiruvathukal, Yung Hsiang Lu
This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC).
1 code implementation • 23 Feb 2024 • Ziheng Jiang, Haibin Lin, Yinmin Zhong, Qi Huang, Yangrui Chen, Zhi Zhang, Yanghua Peng, Xiang Li, Cong Xie, Shibiao Nong, Yulu Jia, Sun He, Hongmin Chen, Zhihao Bai, Qi Hou, Shipeng Yan, Ding Zhou, Yiyao Sheng, Zhuo Jiang, Haohan Xu, Haoran Wei, Zhang Zhang, Pengfei Nie, Leqi Zou, Sida Zhao, Liang Xiang, Zherui Liu, Zhe Li, Xiaoying Jia, Jianxi Ye, Xin Jin, Xin Liu
Training LLMs at this scale brings unprecedented challenges to training efficiency and stability.
no code implementations • 15 Feb 2024 • Jing Su, Chufeng Jiang, Xin Jin, Yuxin Qiao, Tingsong Xiao, Hongda Ma, Rong Wei, Zhi Jing, Jiajun Xu, Junhong Lin
This systematic literature review comprehensively examines the application of Large Language Models (LLMs) in forecasting and anomaly detection, highlighting the current state of research, inherent challenges, and prospective future directions.
no code implementations • 13 Feb 2024 • Xin Jin, Wu Zhou, Jingyu Wang, Duo Xu, Yongsen Zheng
In order to improve the quality of AI music generation and further guide computer music production, synthesis, recommendation and other tasks, we use Birkhoff's aesthetic measure to design a aesthetic model, objectively measuring the aesthetic beauty of music, and form a recommendation list according to the aesthetic feeling of music.
no code implementations • 4 Feb 2024 • Xin Jin, Bohan Li, Baao Xie, Wenyao Zhang, Jinming Liu, Ziqiang Li, Tao Yang, Wenjun Zeng
Representation disentanglement may help AI fundamentally understand the real world and thus benefit both discrimination and generation tasks.
no code implementations • 26 Jan 2024 • Dandan Zhang, Xin Jin, Hongye Su
By designing the decentralized time-regularized (Zeno-free) event-triggered strategies for the state-feedback control law, this paper considers the stochastic stabilization of a class of networked control systems, where two sources of randomness exist in multiple decentralized networks that operate asynchronously and independently: the communication channels are constrained by the stochastic network delays and also by Poisson pulsing denial-of-service (Pp-DoS) attacks.
1 code implementation • 16 Jan 2024 • Mengwei Xu, Wangsong Yin, Dongqi Cai, Rongjie Yi, Daliang Xu, QiPeng Wang, Bingyang Wu, Yihao Zhao, Chen Yang, Shihe Wang, Qiyang Zhang, Zhenyan Lu, Li Zhang, Shangguang Wang, Yuanchun Li, Yunxin Liu, Xin Jin, Xuanzhe Liu
Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment.
no code implementations • 10 Jan 2024 • Huafeng Qin, Hongyu Zhu, Xin Jin, Qun Song, Mounim A. El-Yacoubi, Xinbo Gao
To this end, we propose a mixed block consisting of three modules, transformer, attention Long short-term memory (attention LSTM), and Fourier transformer.
no code implementations • 28 Dec 2023 • Yajing Zhai, Yawen Zeng, Zhiyong Huang, Zheng Qin, Xin Jin, Da Cao
Thereby, this paper explores the potential of using the generated multiple person attributes as prompts in ReID tasks with off-the-shelf (large) models for more accurate retrieval results.
no code implementations • 26 Dec 2023 • Liang Xu, Xintao Lv, Yichao Yan, Xin Jin, Shuwen Wu, Congsheng Xu, Yifan Liu, Yizhou Zhou, Fengyun Rao, Xingdong Sheng, Yunhui Liu, Wenjun Zeng, Xiaokang Yang
We also equip Inter-X with versatile annotations of more than 34K fine-grained human part-level textual descriptions, semantic interaction categories, interaction order, and the relationship and personality of the subjects.
no code implementations • 20 Dec 2023 • Xin Jin, Charalampos Katsis, Fan Sang, Jiahao Sun, Elisa Bertino, Ramana Rao Kompella, Ashish Kundu
In this paper, we propose Graphene, an advanced system designed to provide a detailed analysis of the security posture of computing infrastructures.
2 code implementations • 19 Dec 2023 • Huafeng Qin, Xin Jin, Yun Jiang, Mounim A. El-Yacoubi, Xinbo Gao
In this paper, we propose AdAutomixup, an adversarial automatic mixup augmentation approach that generates challenging samples to train a robust classifier for image classification, by alternatively optimizing the classifier and the mixup sample generator.
1 code implementation • 15 Dec 2023 • Xin Jin, Jonathan Larson, Weiwei Yang, Zhiqiang Lin
Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature.
no code implementations • 12 Dec 2023 • Renyang Liu, Wei Zhou, Xin Jin, Song Gao, Yuanyu Wang, Ruxin Wang
In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually results in thousands of trials during an attack.
1 code implementation • 8 Dec 2023 • Tongxin Hu, Zhuang Li, Xin Jin, Lizhen Qu, Xin Zhang
Annually, e-commerce platforms incur substantial financial losses due to trademark infringements, making it crucial to identify and mitigate potential legal risks tied to merchant information registered to the platforms.
no code implementations • 6 Dec 2023 • Heng Huang, Xin Jin, Yaqi Liu, Hao Lou, Chaoen Xiao, Shuai Cui, Xinning Li, Dongqing Zou
Then, we define an aesthetic attribute contribution to describe the role of aesthetic attributes throughout an image and use it with the attribute scores and the overall scores to train our F2S model.
no code implementations • 31 Oct 2023 • Wei Zhao, Yijun Wang, Tianyu He, Lianying Yin, Jianxin Lin, Xin Jin
To augment the richness of 3D facial animation, we construct a new 3D dataset with detailed shapes and learn to synthesize facial details in line with speech content.
2 code implementations • 28 Sep 2023 • Mingqi Yuan, Zequn Zhang, Yang Xu, Shihao Luo, Bo Li, Xin Jin, Wenjun Zeng
We present RLLTE: a long-term evolution, extremely modular, and open-source framework for reinforcement learning (RL) research and application.
1 code implementation • 15 Sep 2023 • Insu Jang, Zhenning Yang, Zhen Zhang, Xin Jin, Mosharaf Chowdhury
Oobleck enables resilient distributed training of large DNN models with guaranteed fault tolerance.
no code implementations • 8 Sep 2023 • Daliang Xu, Wangsong Yin, Xin Jin, Ying Zhang, Shiyun Wei, Mengwei Xu, Xuanzhe Liu
Currently, the execution of these generative tasks heavily depends on Large Language Models (LLMs).
1 code implementation • ICCV 2023 • Mingde Yao, Jie Huang, Xin Jin, Ruikang Xu, Shenglong Zhou, Man Zhou, Zhiwei Xiong
Existing methods typically work well on their trained lightness conditions but perform poorly in unknown ones due to their limited generalization ability.
1 code implementation • 18 Aug 2023 • Xin Li, Yulin Ren, Xin Jin, Cuiling Lan, Xingrui Wang, Wenjun Zeng, Xinchao Wang, Zhibo Chen
Image restoration (IR) has been an indispensable and challenging task in the low-level vision field, which strives to improve the subjective quality of images distorted by various forms of degradation.
1 code implementation • ICCV 2023 • Xin Jin, Jia-Wen Xiao, Ling-Hao Han, Chunle Guo, Xialei Liu, Chongyi Li, Ming-Ming Cheng
However, these methods are impeded by several critical limitations: a) the explicit calibration process is both labor- and time-intensive, b) challenge exists in transferring denoisers across different camera models, and c) the disparity between synthetic and real noise is exacerbated by digital gain.
Ranked #1 on Image Denoising on SID SonyA7S2 x300
no code implementations • 20 Jul 2023 • Kaiwen Wei, Jie Yao, Jingyuan Zhang, Yangyang Kang, Fubang Zhao, Yating Zhang, Changlong Sun, Xin Jin, Xin Zhang
Firstly, the layout of existing datasets is relatively fixed and limited in the number of semantic entity categories, creating a significant gap between these datasets and the complex real-world scenarios.
no code implementations • 22 Jun 2023 • Bohan Li, Yasheng Sun, Jingxin Dong, Zheng Zhu, Jinming Liu, Xin Jin, Wenjun Zeng
Numerous studies have investigated the pivotal role of reliable 3D volume representation in scene perception tasks, such as multi-view stereo (MVS) and semantic scene completion (SSC).
no code implementations • 20 Jun 2023 • Lianying Yin, Yijun Wang, Tianyu He, Jinming Liu, Wei Zhao, Bohan Li, Xin Jin, Jianxin Lin
In this paper, we present a novel framework (EMoG) to tackle the above challenges with denoising diffusion models: 1) To alleviate the one-to-many problem, we incorporate emotion clues to guide the generation process, making the generation much easier; 2) To model joint correlation, we propose to decompose the difficult gesture generation into two sub-problems: joint correlation modeling and temporal dynamics modeling.
no code implementations • 24 May 2023 • Qi Wang, Junming Yang, Yunbo Wang, Xin Jin, Wenjun Zeng, Xiaokang Yang
Training offline reinforcement learning (RL) models using visual inputs poses two significant challenges, i. e., the overfitting problem in representation learning and the overestimation bias for expected future rewards.
no code implementations • 10 May 2023 • Bingyang Wu, Yinmin Zhong, Zili Zhang, Gang Huang, Xuanzhe Liu, Xin Jin
Based on the new semi information-agnostic setting of LLM inference, the scheduler leverages the input length information to assign an appropriate initial queue for each arrival job to join.
no code implementations • ICCV 2023 • Ruoyu Feng, Yixin Gao, Xin Jin, Runsen Feng, Zhibo Chen
Nevertheless, they divide the input image into multiple rectangular regions according to semantics and ignore avoiding information interaction among them, causing waste of bitrate and distorted reconstruction of region boundaries.
no code implementations • 4 May 2023 • Ruoyu Feng, Jinming Liu, Xin Jin, Xiaohan Pan, Heming Sun, Zhibo Chen
For ICM, developing a unified codec to reduce information redundancy while empowering the compressed features to support various vision tasks is very important, which inevitably faces two core challenges: 1) How should the compression strategy be adjusted based on the downstream tasks?
1 code implementation • 30 Apr 2023 • Kedeng Tong, Xin Jin, Yuqing Yang, Chen Wang, Jinshi Kang, Fan Jiang
Also, it achieves 18. 73% bitrate saving and generates perceptually pleasant reconstructions compared to the state-of-the-art end-to-end image compression methods, which benefits the applications of focused plenoptic cameras greatly.
no code implementations • 25 Apr 2023 • Ban Chen, Xin Jin, Youxin Chen, Longhai Wu, Jie Chen, Jayoon Koo, Cheul-hee Hahm
Extensive experiments show that easy samples pass through fast models while difficult samples inference with heavy models, and our proposed pipeline can improve the accuracy-efficiency trade-off for VFI.
no code implementations • 23 Apr 2023 • Xin Jin, Wu Zhou, Jinyu Wang, Duo Xu, Yiqing Rong, Jialin Sun
In order to guide the generation task of AI music performance, and to improve the performance effect of human performers, this paper uses Birkhoff's aesthetic measure to propose a method of objective measurement of beauty.
1 code implementation • ICCV 2023 • Baao Xie, Bohan Li, Zequn Zhang, Junting Dong, Xin Jin, Jingyu Yang, Wenjun Zeng
They are complementary -- the outer navigation is to identify global-view semantic directions, and the inner refinement dedicates to fine-grained attributes.
no code implementations • 13 Apr 2023 • Letian Wu, Wenyao Zhang, Tengping Jiang, Wankou Yang, Xin Jin, Wenjun Zeng
Based on that, we build upon the CLIP model as a backbone which we extend with a One-Way [CLS] token navigation from text to the visual branch that enables zero-shot dense prediction, dubbed \textbf{ClsCLIP}.
1 code implementation • 13 Apr 2023 • Tao Yu, Runseng Feng, Ruoyu Feng, Jinming Liu, Xin Jin, Wenjun Zeng, Zhibo Chen
We are also very willing to help everyone share and promote new projects based on our Inpaint Anything (IA).
1 code implementation • 24 Mar 2023 • Bohan Li, Yasheng Sun, Zhujin Liang, Dalong Du, Zhuanghui Zhang, XiaoFeng Wang, Yunnan Wang, Xin Jin, Wenjun Zeng
However, due to the inherent representation gap between stereo geometry and BEV features, it is non-trivial to bridge them for dense prediction task of SSC.
no code implementations • 21 Mar 2023 • Xin Jin, Yuchen Wang
The growth of pending legal cases in populous countries, such as India, has become a major issue.
2 code implementations • CVPR 2023 • Xin Li, Bingchen Li, Xin Jin, Cuiling Lan, Zhibo Chen
In this paper, we are the first to propose a novel training strategy for image restoration from the causality perspective, to improve the generalization ability of DNNs for unknown degradations.
6 code implementations • 10 Mar 2023 • Kedeng Tong, Yaojun Wu, Yue Li, Kai Zhang, Li Zhang, Xin Jin
In this paper, we present a Quantization-error-aware Variable Rate Framework (QVRF) that utilizes a univariate quantization regulator a to achieve wide-range variable rates within a single model.
1 code implementation • 25 Feb 2023 • Yaqi Liu, Binbin Lv, Xin Jin, Xiaoyu Chen, Xiaokun Zhang
In this paper, we propose a Transformer-style network with two feature extraction branches for image forgery localization, and it is named as Two-Branch Transformer (TBFormer).
2 code implementations • 22 Feb 2023 • Zhuohan Li, Lianmin Zheng, Yinmin Zhong, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E. Gonzalez, Ion Stoica
Model parallelism is conventionally viewed as a method to scale a single large deep learning model beyond the memory limits of a single device.
1 code implementation • 1 Feb 2023 • Guanqi Ding, Xinzhe Han, Shuhui Wang, Xin Jin, Dandan Tu, Qingming Huang
SAGE takes use of all given few-shot images and estimates a class center embedding based on the category-relevant attribute dictionary.
1 code implementation • 26 Jan 2023 • Mingqi Yuan, Bo Li, Xin Jin, Wenjun Zeng
We present AIRS: Automatic Intrinsic Reward Shaping that intelligently and adaptively provides high-quality intrinsic rewards to enhance exploration in reinforcement learning (RL).
no code implementations • 14 Jan 2023 • Xin Jin, Wu Zhou, Jinyu Wang, Duo Xu, Yiqing Rong, Shuai Cui
Computational aesthetics evaluation has made great achievements in the field of visual arts, but the research work on music still needs to be explored.
2 code implementations • CVPR 2023 • Xin Jin, Ling-Hao Han, Zhen Li, Chun-Le Guo, Zhi Chai, Chongyi Li
The exclusive properties of RAW data have shown great potential for low-light image enhancement.
1 code implementation • CVPR 2023 • Qian Li, Yuxiao Hu, Ye Liu, Dongxiao Zhang, Xin Jin, Yuntian Chen
Classical adversarial attacks for Face Recognition (FR) models typically generate discrete examples for target identity with a single state image.
1 code implementation • 6 Dec 2022 • Haoyang He, Xin Jin, Angela Chen
Generating new fonts is a time-consuming and labor-intensive task, especially in a language with a huge amount of characters like Chinese.
no code implementations • 28 Nov 2022 • Mingqi Yuan, Xin Jin, Bo Li, Wenjun Zeng
We present MEM: Multi-view Exploration Maximization for tackling complex visual control tasks.
1 code implementation • CVPR 2023 • Tao Yu, Zhihe Lu, Xin Jin, Zhibo Chen, Xinchao Wang
Large-scale vision-language models (VLMs) pre-trained on billion-level data have learned general visual representations and broad visual concepts.
1 code implementation • CVPR 2023 • Xin Jin, Longhai Wu, Jie Chen, Youxin Chen, Jayoon Koo, Cheul-hee Hahm
Cast in a flexible pyramid framework, UPR-Net exploits lightweight recurrent modules for both bi-directional flow estimation and intermediate frame synthesis.
Ranked #2 on Video Frame Interpolation on MSU Video Frame Interpolation (PSNR metric)
no code implementations • 19 Sep 2022 • Mingqi Yuan, Bo Li, Xin Jin, Wenjun Zeng
Exploration is critical for deep reinforcement learning in complex environments with high-dimensional observations and sparse rewards.
1 code implementation • 16 Sep 2022 • Lin Chen, Zhixiang Wei, Xin Jin, Huaian Chen, Miao Zheng, Kai Chen, Yi Jin
In this work, we resort to data mixing to establish a deliberated domain bridging (DDB) for DASS, through which the joint distributions of source and target domains are aligned and interacted with each in the intermediate space.
Ranked #1 on Domain Adaptation on GTAV+Synscapes to Cityscapes
no code implementations • 22 Aug 2022 • Xiaobo Gao, Qi Kuang, Xin Jin, Bin Zhou, Boyan Dong, Xunyu Wang
Then we propose a time-lapse photography interface to facilitate users to view and adjust parameters and use virtual robots to conduct virtual photography in a three-dimensional scene.
no code implementations • 19 Aug 2022 • Changzhen Li, Jie Zhang, Shuzhe Wu, Xin Jin, Shiguang Shan
Recently action recognition has received more and more attention for its comprehensive and practical applications in intelligent surveillance and human-computer interaction.
1 code implementation • 14 Aug 2022 • Chunle Guo, Ruiqi Wu, Xin Jin, Linghao Han, Zhi Chai, Weidong Zhang, Chongyi Li
To achieve that, we also contribute a dataset, URankerSet, containing sufficient results enhanced by different UIE algorithms and the corresponding perceptual rankings, to train our URanker.
no code implementations • 10 Aug 2022 • Xin Jin, Wu Zhou, Xinghui Zhou, Shuai Cui, Le Zhang, Jianwen Lv, Shu Zhao
In this paper, we propose a new task of aesthetic language assessment: aesthetic visual question and answering (AVQA) of images.
no code implementations • 9 Aug 2022 • Xin Jin, Qiang Deng, Jianwen Lv, Heng Huang, Hao Lou, Chaoen Xiao
The differences of the three attributes between the input images and the photography templates or the guidance images are described in natural language, which is aesthetic natural language guidance (ALG).
no code implementations • 9 Aug 2022 • Xinghui Zhou, Xin Jin, Jianwen Lv, Heng Huang, Ming Mao, Shuai Cui
In this paper, we propose aesthetic attribute assessment, which is the aesthetic attributes captioning, i. e., to assess the aesthetic attributes such as composition, lighting usage and color arrangement.
no code implementations • 9 Aug 2022 • Xin Jin, Shu Zhao, Le Zhang, Xin Zhao, Qiang Deng, Chaoen Xiao
In recent years, image generation has made great strides in improving the quality of images, producing high-fidelity ones.
1 code implementation • 17 Jul 2022 • Jingwen Ye, Yifang Fu, Jie Song, Xingyi Yang, Songhua Liu, Xin Jin, Mingli Song, Xinchao Wang
Life-long learning aims at learning a sequence of tasks without forgetting the previously acquired knowledge.
3 code implementations • 5 Jul 2022 • Xin Jin, Xinning Li, Hao Lou, Chenyu Fan, Qiang Deng, Chaoen Xiao, Shuai Cui, Amit Kumar Singh
Besides, we propose a efficient method for image aesthetic attribute assessment on mixed multi-attribute dataset and construct a multitasking network architecture by using the EfficientNet-B0 as the backbone network.
no code implementations • 5 Jul 2022 • Ruoyu Feng, Xin Jin, Zongyu Guo, Runsen Feng, Yixin Gao, Tianyu He, Zhizheng Zhang, Simeng Sun, Zhibo Chen
Learning a kind of feature that is both general (for AI tasks) and compact (for compression) is pivotal for its success.
no code implementations • 30 Jun 2022 • Dandan Zhang, Xin Jin, Hongye Su
This paper reviews the attitude control problems for rigid-body systems, starting from the attitude representation for rigid body kinematics.
no code implementations • 20 Jun 2022 • Yanru Jiang, Xin Jin, Qinhao Deng
This study concludes that while short-form video platforms could potentially challenge the protest paradigm on the content creators' side, the audiences' preference as measured by social media visibility might still be moderately associated with the protest paradigm.
1 code implementation • 17 Jun 2022 • Xin Jin, Longhai Wu, Guotao Shen, Youxin Chen, Jie Chen, Jayoon Koo, Cheul-hee Hahm
We present a novel simple yet effective algorithm for motion-based video frame interpolation.
Ranked #3 on Video Frame Interpolation on MSU Video Frame Interpolation (LPIPS metric)
no code implementations • 14 Jun 2022 • Xin Jin, Charalampos Katsis, Fan Sang, Jiahao Sun, Ashish Kundu, Ramana Kompella
Edge computing is a paradigm that shifts data processing services to the network edge, where data are generated.
1 code implementation • CVPR 2022 • Lin Chen, Huaian Chen, Zhixiang Wei, Xin Jin, Xiao Tan, Yi Jin, Enhong Chen
Such NWD can be coupled with the classifier to serve as a discriminator satisfying the K-Lipschitz constraint without the requirements of additional weight clipping or gradient penalty strategy.
Ranked #2 on Domain Adaptation on ImageCLEF-DA
1 code implementation • 2 Apr 2022 • Zhenhuan Liu, Liang Li, Huajie Jiang, Xin Jin, Dandan Tu, Shuhui Wang, Zheng-Jun Zha
Furthermore, we devise the spatio-temporal correlative map as a style-independent, global-aware regularization on the perceptual motion consistency.
1 code implementation • CVPR 2022 • Guanqi Ding, Xinzhe Han, Shuhui Wang, Shuzhe Wu, Xin Jin, Dandan Tu, Qingming Huang
Few-shot image generation is a challenging task even using the state-of-the-art Generative Adversarial Networks (GANs).
no code implementations • ICCV 2023 • Liang Xu, Ziyang Song, Dongliang Wang, Jing Su, Zhicheng Fang, Chenjing Ding, Weihao Gan, Yichao Yan, Xin Jin, Xiaokang Yang, Wenjun Zeng, Wei Wu
We present a GAN-based Transformer for general action-conditioned 3D human motion generation, including not only single-person actions but also multi-person interactive actions.
no code implementations • 14 Mar 2022 • Xing Chu, Zhi Liu, Lei Mao, Xin Jin, Zhaoxia Peng, Guoguang Wen
In this brief, an improved event-triggered update mechanism (ETM) for the linear quadratic regulator is proposed to solve the lateral motion control problem of intelligent vehicle under bounded disturbances.
2 code implementations • 22 Feb 2022 • Kedeng Tong, Xin Jin, Chen Wang, Fan Jiang
Light field image becomes one of the most promising media types for immersive video applications.
no code implementations • 25 Jan 2022 • Xin Jin, Ruoyu Feng, Simeng Sun, Runsen Feng, Tianyu He, Zhibo Chen
Traditional media coding schemes typically encode image/video into a semantic-unknown binary stream, which fails to directly support downstream intelligent tasks at the bitstream level.
no code implementations • 8 Jan 2022 • Xin Jin, Hao Lou, Huang Heng, XiaoDong Li, Shuai Cui, Xiaokun Zhang, Xiqiao Li
In the tasks of image aesthetic quality evaluation, it is difficult to reach both the high score area and low score area due to the normal distribution of aesthetic datasets.
no code implementations • CVPR 2022 • Zizheng Yang, Xin Jin, Kecheng Zheng, Feng Zhao
During the pre-training, we attempt to address two critical issues for learning fine-grained ReID features: (1) the augmentations in CL pipeline may distort the discriminative clues in person images.
1 code implementation • 26 Dec 2021 • Zongyu Guo, Runsen Feng, Zhizheng Zhang, Xin Jin, Zhibo Chen
Neural video codecs have demonstrated great potential in video transmission and storage applications.
2 code implementations • 16 Dec 2021 • Paul Bergmann, Xin Jin, David Sattlegger, Carsten Steger
We introduce the first comprehensive 3D dataset for the task of unsupervised anomaly detection and localization.
3D Anomaly Detection and Segmentation Depth Anomaly Detection and Segmentation +4
1 code implementation • 1 Dec 2021 • Zizheng Yang, Xin Jin, Kecheng Zheng, Feng Zhao
During the pre-training, we attempt to address two critical issues for learning fine-grained ReID features: (1) the augmentations in CL pipeline may distort the discriminative clues in person images.
no code implementations • 26 Nov 2021 • Xin Li, Zhizheng Zhang, Guoqiang Wei, Cuiling Lan, Wenjun Zeng, Xin Jin, Zhibo Chen
In this paper, we propose a novel Confounder Identification-free Causal Visual Feature Learning (CICF) method, which obviates the need for identifying confounders.
no code implementations • 25 Nov 2021 • Xin Li, Xin Jin, Jun Fu, Xiaoyuan Yu, Bei Tong, Zhibo Chen
Under this brand-new scenario, we propose Distortion Relation guided Transfer Learning (DRTL) for the few-shot RealSR by transferring the rich restoration knowledge from auxiliary distortions (i. e., synthetic distortions) to the target RealSR under the guidance of distortion relation.
no code implementations • 19 Nov 2021 • Xin Jin, Tianyu He, Xu Shen, Tongliang Liu, Xinchao Wang, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua
Unsupervised Person Re-identification (U-ReID) with pseudo labeling recently reaches a competitive performance compared to fully-supervised ReID methods based on modern clustering algorithms.
no code implementations • 7 Oct 2021 • Gaojian Wang, Qian Jiang, Xin Jin, Wei Li, Xiaohui Cui
Moreover, we make a key observation that subtle forgery artifacts can be further exposed in the patch-wise phase and amplitude spectrum and exhibit different clues.
no code implementations • 29 Sep 2021 • Xin Jin, Tianyu He, Xu Shen, Songhua Wu, Tongliang Liu, Xinchao Wang, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua
In this paper, we propose an embarrassing simple yet highly effective adversarial domain adaptation (ADA) method for effectively training models for alignment.
no code implementations • 29 Sep 2021 • Xu Cheng, Xin Wang, Haotian Xue, Zhengyang Liang, Xin Jin, Quanshi Zhang
This paper proposes a hypothesis to analyze the underlying reason for the cognitive difficulty of an image from two perspectives, i. e. a cognitive image usually makes a DNN strongly activated by cognitive concepts; discarding massive non-cognitive concepts may also help the DNN focus on cognitive concepts.
1 code implementation • 14 Aug 2021 • Xin Jin, Zhonglan Li, Ke Liu, Dongqing Zou, XiaoDong Li, Xingfan Zhu, Ziyin Zhou, Qilong Sun, Qingyu Liu
Classification sub-module supplies classifying of images according to the eras, nationalities and garment types; Parsing sub-network supplies the semantic for person contours, clothing and background in the image to achieve more accurate colorization of clothes and persons and prevent color overflow.
1 code implementation • 5 Jul 2021 • Gaojian Wang, Qian Jiang, Xin Jin, Xiaohui Cui
The internet is filled with fake face images and videos synthesized by deep generative models.
no code implementations • 24 Jun 2021 • Xin Jin, Ji-Eun Lee, Charley Schaefer, Xinwei Luo, Adam J. M. Wollman, Alex L. Payne-Dwyer, Tian Tian, Xiaowei Zhang, Xiao Chen, Yingxing Li, Tom C. B. McLeish, Mark C. Leake, Fan Bai
Liquid-liquid phase separation is emerging as a crucial phenomenon in several fundamental cell processes.
no code implementations • 24 May 2021 • Xin Jin
This paper presents a framework of imitating the principal investor's behavior for optimal pricing and hedging options.
1 code implementation • CVPR 2022 • Xin Jin, Tianyu He, Kecheng Zheng, Zhiheng Yin, Xu Shen, Zhen Huang, Ruoyu Feng, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen
Specifically, we introduce Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, we name this framework as GI-ReID.
Ranked #5 on Person Re-Identification on PRCC
Cloth-Changing Person Re-Identification Computational Efficiency +1
no code implementations • ICCV 2021 • Xin Jin, Cuiling Lan, Wenjun Zeng, Zhibo Chen
Many unsupervised domain adaptation (UDA) methods exploit domain adversarial training to align the features to reduce domain gap, where a feature extractor is trained to fool a domain discriminator in order to have aligned feature distributions.
2 code implementations • 20 Mar 2021 • Shiqi Lin, Tao Yu, Ruoyu Feng, Xin Li, Xin Jin, Zhibo Chen
We formulate it as a multi-agent reinforcement learning (MARL) problem, where each agent learns an augmentation policy for each patch based on its content together with the semantics of the whole image.
no code implementations • ICCV 2021 • Tianyu He, Xin Jin, Xu Shen, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua
The CNN encoder is responsible for efficiently extracting discriminative spatial features while the DI decoder is designed to densely model spatial-temporal inherent interaction across frames.
Ranked #1 on Person Re-Identification on DukeMTMC-reID
1 code implementation • 3 Jan 2021 • Xin Jin, Cuiling Lan, Wenjun Zeng, Zhibo Chen
In this paper, we design a novel Style Normalization and Restitution module (SNR) to simultaneously ensure both high generalization and discrimination capability of the networks.
no code implementations • 19 Dec 2020 • Xin Jin, Hongyu Zhang, XiaoDong Li, Haoyang Yu, Beisheng Liu, Shujiang Xie, Amit Kumar Singh, Yujie Li
To make this algorithm easy to use, we also designed and implemented an efficient general blind computing library based on CMP-SWHE.
no code implementations • 17 Dec 2020 • Yaojun Wu, Xin Li, Zhizheng Zhang, Xin Jin, Zhibo Chen
Recent works on learned image compression perform encoding and decoding processes in a full-resolution manner, resulting in two problems when deployed for practical applications.
no code implementations • 11 Dec 2020 • Xin Li, Xin Jin, Tao Yu, Yingxue Pang, Simeng Sun, Zhizheng Zhang, Zhibo Chen
Traditional single image super-resolution (SISR) methods that focus on solving single and uniform degradation (i. e., bicubic down-sampling), typically suffer from poor performance when applied into real-world low-resolution (LR) images due to the complicated realistic degradations.
1 code implementation • 4 Nov 2020 • Qi Kuang, Xin Jin, Qinping Zhao, Bin Zhou
Our model can judge whether a UAV video was shot by professional photographers or amateurs together with the scene type classification.
no code implementations • 15 Oct 2020 • Xin Jin, Xiqiao Li, Heng Huang, XiaoDong Li, Xinghui Zhou
In this paper, we propose a Deep Drift-Diffusion (DDD) model inspired by psychologists to predict aesthetic score distribution from images.
no code implementations • 30 Sep 2020 • Yingxue Pang, Xin Li, Xin Jin, Yaojun Wu, Jianzhao Liu, Sen Liu, Zhibo Chen
Specifically, we extract different frequencies of the LR image and pass them to a channel attention-grouped residual dense network (CA-GRDB) individually to output corresponding feature maps.
no code implementations • ICML 2020 • Yu Chen, Zhenming Liu, Bin Ren, Xin Jin
Efficient construction of checkpoints/snapshots is a critical tool for training and diagnosing deep learning models.
no code implementations • 25 Sep 2020 • Pengxu Wei, Hannan Lu, Radu Timofte, Liang Lin, WangMeng Zuo, Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding, Tangxin Xie, Liang Cao, Yan Zou, Yi Shen, Jialiang Zhang, Yu Jia, Kaihua Cheng, Chenhuan Wu, Yue Lin, Cen Liu, Yunbo Peng, Xueyi Zou, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Tongtong Zhao, Shanshan Zhao, Yoseob Han, Byung-Hoon Kim, JaeHyun Baek, HaoNing Wu, Dejia Xu, Bo Zhou, Wei Guan, Xiaobo Li, Chen Ye, Hao Li, Yukai Shi, Zhijing Yang, Xiaojun Yang, Haoyu Zhong, Xin Li, Xin Jin, Yaojun Wu, Yingxue Pang, Sen Liu, Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li, Marie-Paule Cani, Wan-Chi Siu, Yuanbo Zhou, Rao Muhammad Umer, Christian Micheloni, Xiaofeng Cong, Rajat Gupta, Keon-Hee Ahn, Jun-Hyuk Kim, Jun-Ho Choi, Jong-Seok Lee, Feras Almasri, Thomas Vandamme, Olivier Debeir
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020.
no code implementations • ECCV 2020 • Zhao-Min Chen, Xin Jin, Borui Zhao, Xiu-Shen Wei, Yanwen Guo
To address this issue, we present a simple but effective Hierarchical Context Embedding (HCE) framework, which can be applied as a plug-and-play component, to facilitate the classification ability of a series of region-based detectors by mining contextual cues.
no code implementations • ECCV 2020 • Xin Li, Xin Jin, Jianxin Lin, Tao Yu, Sen Liu, Yaojun Wu, Wei Zhou, Zhibo Chen
Hybrid-distorted image restoration (HD-IR) is dedicated to restore real distorted image that is degraded by multiple distortions.
no code implementations • 22 Jun 2020 • Xin Jin, Cuiling Lan, Wen-Jun Zeng, Zhibo Chen
To ensure high discrimination, we propose a Feature Restoration (FR) operation to distill task-relevant features from the residual information and use them to compensate for the aligned features.
Ranked #73 on Domain Generalization on PACS
1 code implementation • 17 Jun 2020 • Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora, Xin Jin
As such, we advocate that the real challenge of distributed training is for the network community to develop high-performance network transport to fully utilize the network capacity and achieve linear scale-out.
no code implementations • ECCV 2020 • Xin Jin, Cuiling Lan, Wen-Jun Zeng, Zhibo Chen
To address this problem, we introduce a global distance-distributions separation (GDS) constraint over the two distributions to encourage the clear separation of positive and negative samples from a global view.
1 code implementation • CVPR 2020 • Xin Jin, Cuiling Lan, Wen-Jun Zeng, Zhibo Chen, Li Zhang
Existing fully-supervised person re-identification (ReID) methods usually suffer from poor generalization capability caused by domain gaps.
Ranked #8 on Unsupervised Domain Adaptation on Market to Duke
no code implementations • LREC 2020 • Xian Huang, Xin Jin, Qike Li, Keliang Zhang
An Automatic Speech Recognition (ASR) system simply trained on British English (BE) /American English (AE) speech data and using the BE/AE pronunciation dictionary performs much worse when applied to IE.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • CVPR 2020 • Chang-Dong Xu, Xing-Ran Zhao, Xin Jin, Xiu-Shen Wei
Specifically, by integrating an image-level multi-label classifier upon the detection backbone, we can obtain the sparse but crucial image regions corresponding to categorical information, thanks to the weakly localization ability of the classification manner.
no code implementations • 15 Jan 2020 • Xin Jin, Cuiling Lan, Wen-Jun Zeng, Zhibo Chen
To the best of our knowledge, we are the first to make use of multi-shots of an object in a teacher-student learning manner for effectively boosting the single image based re-id.
1 code implementation • 23 Nov 2019 • Tao Yu, Zongyu Guo, Xin Jin, Shilin Wu, Zhibo Chen, Weiping Li, Zhizheng Zhang, Sen Liu
In this work, we show that the mean and variance shifts caused by full-spatial FN limit the image inpainting network training and we propose a spatial region-wise normalization named Region Normalization (RN) to overcome the limitation.
2 code implementations • 11 Jul 2019 • Xin Jin, Le Wu, Geng Zhao, Xiao-Dong Li, Xiaokun Zhang, Shiming Ge, Dongqing Zou, Bin Zhou, Xinghui Zhou
This is a new formula of image aesthetic assessment, which predicts aesthetic attributes captions together with the aesthetic score of each attribute.
no code implementations • 8 Jul 2019 • Xin Jin, Rui Han, Ning Ning, Xiao-Dong Li, Xiaokun Zhang
To meet the women appearance needs, we present a novel virtual experience approach of facial makeup transfer, developed into windows platform application software.
1 code implementation • 27 Jun 2019 • Longbin Lai, Zhu Qing, Zhengyi Yang, Xin Jin, Zhengmin Lai, Ran Wang, Kongzhang Hao, Xuemin Lin, Lu Qin, Wenjie Zhang, Ying Zhang, Zhengping Qian, Jingren Zhou
We conduct extensive experiments for both unlabelled matching and labelled matching to analyze the performance of distributed subgraph matching under various settings, which is finally summarized as a practical guide.
Databases
1 code implementation • 30 May 2019 • Xin Jin, Cuiling Lan, Wen-Jun Zeng, Guoqiang Wei, Zhibo Chen
Specifically, we build a Semantics Aligning Network (SAN) which consists of a base network as encoder (SA-Enc) for re-ID, and a decoder (SA-Dec) for reconstructing/regressing the densely semantics aligned full texture image.
no code implementations • 18 Apr 2019 • Hang Zhu, Zhihao Bai, Jialin Li, Ellis Michael, Dan Ports, Ion Stoica, Xin Jin
Experimental results show that Harmonia improves the throughput of these protocols by up to 10X for a replication factor of 10, providing near-linear scalability up to the limit of our testbed.
Distributed, Parallel, and Cluster Computing
no code implementations • 17 Apr 2019 • Xin Jin, Cuiling Lan, Wen-Jun Zeng, Zhizheng Zhang, Zhibo Chen
We achieve this by the context interaction among the features of different scales.
1 code implementation • CVPR 2020 • Zhizheng Zhang, Cuiling Lan, Wen-Jun Zeng, Xin Jin, Zhibo Chen
For person re-identification (re-id), attention mechanisms have become attractive as they aim at strengthening discriminative features and suppressing irrelevant ones, which matches well the key of re-id, i. e., discriminative feature learning.
no code implementations • 27 Feb 2019 • Eric Liang, Hang Zhu, Xin Jin, Ion Stoica
First, many of the existing solutions are iteratively building a decision tree by splitting nodes in the tree.
2 code implementations • 14 Feb 2019 • Peng Wang, Hong Xu, Xin Jin, Tao Wang
Mice payments are directly sent by looking up a routing table with a few precomputed paths to reduce probing overhead.
Networking and Internet Architecture
no code implementations • 21 Nov 2018 • Xin Jin, Zhibo Chen, Jianxin Lin, Zhikai Chen, Wei Zhou
Most existing single image deraining methods require learning supervised models from a large set of paired synthetic training data, which limits their generality, scalability and practicality in real-world multimedia applications.
no code implementations • 9 Nov 2018 • Ji Zhao, Zhiqiang Chen, Li Zhang, Xin Jin
In this paper, we propose a sinogram inpainting network (SIN) to solve limited-angle CT reconstruction problem, which is a very challenging ill-posed issue and of great interest for several clinical applications.
Medical Physics Image and Video Processing
no code implementations • 26 Apr 2018 • Zhibo Chen, Tianyu He, Xin Jin, Feng Wu
One key challenge to learning-based video compression is that motion predictive coding, a very effective tool for video compression, can hardly be trained into a neural network.
Multimedia Image and Video Processing
no code implementations • 25 Sep 2017 • Xin Jin, Shuyun Zhu, Le Wu, Geng Zhao, Xiao-Dong Li, Quan Zhou, Huimin Lu
In this work, a multi-level chaotic maps models for 3D textured encryption was presented by observing the different contributions for recognizing cipher 3D models between vertices (point cloud), polygons and textures.
no code implementations • 23 Aug 2017 • Xin Jin, Yannan Li, Ningning Liu, Xiao-Dong Li, Xianggang Jiang, Chaoen Xiao, Shiming Ge
We propose a novel outdoor scene relighting method, which needs only a single reference image and is based on material constrained layer decomposition.
2 code implementations • 23 Aug 2017 • Xin Jin, Le Wu, Xiao-Dong Li, Siyu Chen, Siwei Peng, Jingying Chi, Shiming Ge, Chenggen Song, Geng Zhao
Thus, a novel CNN based on the Cumulative distribution with Jensen-Shannon divergence (CJS-CNN) is presented to predict the aesthetic score distribution of human ratings, with a new reliability-sensitive learning method based on the kurtosis of the score distribution, which eliminates the requirement of the original full data of human ratings (without normalization).
no code implementations • 9 Aug 2017 • Xin Jin, Shiming Ge, Chenggen Song
The experimental results reveal that our protocol can successfully retrieve the proper photos from the cloud server and protect the user photos and the face detector.
no code implementations • 27 Feb 2017 • Xin Jin, Peng Yuan, Xiao-Dong Li, Chenggen Song, Shiming Ge, Geng Zhao, Yingya Chen
Only the base images are submitted randomly to the cloud server.
2 code implementations • 7 Oct 2016 • Xin Jin, Le Wu, Xiao-Dong Li, Xiaokun Zhang, Jingying Chi, Siwei Peng, Shiming Ge, Geng Zhao, Shuying Li
Thus, it is easy to use a pre-trained GoogLeNet for large-scale image classification problem and fine tune our connected layers on an large scale database of aesthetic related images: AVA, i. e. \emph{domain adaptation}.
no code implementations • 15 Aug 2016 • Xin Jin, Xiaoyang Tan
Over the last two decades, face alignment or localizing fiducial facial points has received increasing attention owing to its comprehensive applications in automatic face analysis.