no code implementations • 7 May 2024 • Raiyan Rahman, Christopher Indris, Goetz Bramesfeld, Tianxiao Zhang, Kaidong Li, Xiangyu Chen, Ivan Grijalva, Brian McCornack, Daniel Flippo, Ajay Sharda, Guanghui Wang
In this study, we trained and evaluated four real-time semantic segmentation models and three object detection models specifically for aphid cluster segmentation and detection.
1 code implementation • 21 Apr 2024 • Genggeng Chen, Kexin Dai, Kangzhen Yang, Tao Hu, Xiangyu Chen, Yongqing Yang, Wei Dong, Peng Wu, Yanning Zhang, Qingsen Yan
Specifically, we employ two modules for feature extraction: shared weight modules and non-shared weight modules.
no code implementations • 18 Mar 2024 • Xiangyu Chen, Jing Liu, Ye Wang, Pu, Wang, Matthew Brand, Guanghui Wang, Toshiaki Koike-Akino
Low-rank adaptation (LoRA) and its variants are widely employed in fine-tuning large models, including large language models for natural language processing and diffusion models for computer vision.
1 code implementation • 14 Mar 2024 • Yuhang Zheng, Xiangyu Chen, Yupeng Zheng, Songen Gu, Runyi Yang, Bu Jin, Pengfei Li, Chengliang Zhong, Zengmao Wang, Lina Liu, Chao Yang, Dawei Wang, Zhen Chen, Xiaoxiao Long, Meiqing Wang
In particular, we propose an Efficient Feature Distillation (EFD) module that employs contrastive learning to efficiently and accurately distill language embeddings derived from foundational models.
no code implementations • 14 Dec 2023 • Shuning Xu, Binbin Song, Xiangyu Chen, Xina Liu, Jiantao Zhou
Moire patterns frequently appear when capturing screens with smartphones or cameras, potentially compromising image quality.
1 code implementation • 18 Oct 2023 • Xiangyu Chen, Zheyuan Li, Yuandong Pu, Yihao Liu, Jiantao Zhou, Yu Qiao, Chao Dong
Following this, we present the benchmark results and analyze the reasons behind the performance disparity of different models across various tasks.
no code implementations • 16 Oct 2023 • Yihao Liu, Xiangyu Chen, Xianzheng Ma, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong
To address this issue, we propose a universal model for general image processing that covers image restoration, image enhancement, image feature extraction tasks, etc.
2 code implementations • 11 Sep 2023 • Xiangyu Chen, Xintao Wang, Wenlong Zhang, Xiangtao Kong, Yu Qiao, Jiantao Zhou, Chao Dong
In the training stage, we additionally adopt a same-task pre-training strategy to further exploit the potential of the model for further improvement.
2 code implementations • 8 Sep 2023 • Xiangyu Chen, Zheyuan Li, Zhengwen Zhang, Jimmy S. Ren, Yihao Liu, Jingwen He, Yu Qiao, Jiantao Zhou, Chao Dong
However, the majority of available resources are still in standard dynamic range (SDR).
1 code implementation • 8 Sep 2023 • Shuning Xu, Xiangyu Chen, Binbin Song, Jiantao Zhou
Capturing images with incorrect exposure settings fails to deliver a satisfactory visual experience.
1 code implementation • 6 Sep 2023 • Wenlong Zhang, Xiaohui Li, Xiangyu Chen, Yu Qiao, Xiao-Ming Wu, Chao Dong
In particular, we cluster the extensive degradation space to create a set of representative degradation cases, which serves as a comprehensive test set.
1 code implementation • 25 Aug 2023 • Shuning Xu, Binbin Song, Xiangyu Chen, Jiantao Zhou
In TDR, we propose a temporal-guided bilateral learning pipeline to mitigate the degradation of color and details caused by the moire patterns while preserving the restored frequency information in FDDA.
1 code implementation • 24 Aug 2023 • Xiangyu Chen, Ruiwen Zhen, Shuai Li, Xiaotian Li, Guanghui Wang
Extensive experiments demonstrate that our approach decreases runtime by up to 13% and reduces the number of parameters by up to 23%, while increasing PSNR and SSIM on several image restoration datasets.
no code implementations • 10 Aug 2023 • Tianxiao Zhang, Kaidong Li, Xiangyu Chen, Cuncong Zhong, Bo Luo, Ivan Grijalva, Brian McCornack, Daniel Flippo, Ajay Sharda, Guanghui Wang
To facilitate the use of machine learning models, we further process the images by cropping them into patches, resulting in a labeled dataset comprising 151, 380 image patches.
1 code implementation • ICCV 2023 • Binbin Song, Xiangyu Chen, Shuning Xu, Jiantao Zhou
With the physical model of the scattering effect, we improve the image formation pipeline for the image synthesis to construct a realistic UDC dataset with ground truths.
no code implementations • 12 Jul 2023 • Tianxiao Zhang, Kaidong Li, Xiangyu Chen, Cuncong Zhong, Bo Luo, Ivan Grijalva Teran, Brian McCornack, Daniel Flippo, Ajay Sharda, Guanghui Wang
Aphids are one of the main threats to crops, rural families, and global food security.
1 code implementation • 5 Jul 2023 • Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li, Ying Shan, Jiantao Zhou, Chao Dong
After detecting the artifact regions, we develop a finetune procedure to improve GAN-based SR models with a few samples, so that they can deal with similar types of artifacts in more unseen real data.
no code implementations • 26 May 2023 • Tianxiao Zhang, Andrés M. Bur, Shannon Kraft, Hannah Kavookjian, Bryan Renslo, Xiangyu Chen, Bo Luo, Guanghui Wang
In this study, we made the first endeavor to employ deep learning models to predict patient demographic information to improve detector model performance.
1 code implementation • 27 Mar 2023 • Xiangyu Chen, Varsha Kishore, Kilian Q Weinberger
Image steganography is the process of concealing secret information in images through imperceptible changes.
1 code implementation • 25 Oct 2022 • Xiangyu Chen, Ying Qin, Wenju Xu, Andrés M. Bur, Cuncong Zhong, Guanghui Wang
To boost the performance of vision Transformers on small datasets, this paper proposes to explicitly increase the input information density in the frequency domain.
1 code implementation • 22 Oct 2022 • Xiangyu Chen, Qinghao Hu, Kaidong Li, Cuncong Zhong, Guanghui Wang
After carefully examining the self-attention modules, we discover that the number of trivial attention weights is far greater than the important ones and the accumulated trivial weights are dominating the attention in Vision Transformers due to their large quantity, which is not handled by the attention itself.
1 code implementation • 19 Oct 2022 • Ruihan Wu, Xiangyu Chen, Chuan Guo, Kilian Q. Weinberger
Gradient inversion attack enables recovery of training samples from model gradients in federated learning (FL), and constitutes a serious threat to data privacy.
1 code implementation • 12 Oct 2022 • Lin Zhou, Haoming Cai, Jinjin Gu, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Yu Qiao, Chao Dong
In this work, we design an efficient SR network by improving the attention mechanism.
1 code implementation • 5 Sep 2022 • Xina Liu, JinFan Hu, Xiangyu Chen, Chao Dong
Particularly, flare and blur in UDC images could severely deteriorate the user experience in high dynamic range (HDR) scenes.
no code implementations • 25 Aug 2022 • Xiangyu Chen, Zolboo Byambadorj, Takeaki Yajima, Hisashi Inoue, Isao H. Inoue, Tetsuya Iizuka
The proposed neuron and synapse occupy the area of 127 {\mu}m^{ 2} and 231 {\mu}m^{ 2}, respectively, while achieving millisecond time constants.
no code implementations • 23 Aug 2022 • Lin Liu, Junfeng An, Jianzhuang Liu, Shanxin Yuan, Xiangyu Chen, Wengang Zhou, Houqiang Li, Yanfeng Wang, Qi Tian
Low-light video enhancement (LLVE) is an important yet challenging task with many applications such as photographing and autonomous driving.
no code implementations • CVPR 2022 • Carlos A. Diaz-Ruiz, Youya Xia, Yurong You, Jose Nino, Junan Chen, Josephine Monica, Xiangyu Chen, Katie Luo, Yan Wang, Marc Emond, Wei-Lun Chao, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell
Advances in perception for self-driving cars have accelerated in recent years due to the availability of large-scale datasets, typically collected at specific locations and under nice weather conditions.
no code implementations • 25 May 2022 • Eduardo Pérez-Pellitero, Sibi Catley-Chandar, Richard Shaw, Aleš Leonardis, Radu Timofte, Zexin Zhang, Cen Liu, Yunbo Peng, Yue Lin, Gaocheng Yu, Jin Zhang, Zhe Ma, Hongbin Wang, Xiangyu Chen, Xintao Wang, Haiwei Wu, Lin Liu, Chao Dong, Jiantao Zhou, Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong, Dan Zhu, Mengdi Sun, Guannan Chen, Yang Hu, Haowei Li, Baozhu Zou, Zhen Liu, Wenjie Lin, Ting Jiang, Chengzhi Jiang, Xinpeng Li, Mingyan Han, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Juan Marín-Vega, Michael Sloth, Peter Schneider-Kamp, Richard Röttger, Chunyang Li, Long Bao, Gang He, Ziyao Xu, Li Xu, Gen Zhan, Ming Sun, Xing Wen, Junlin Li, Shuang Feng, Fei Lei, Rui Liu, Junxiang Ruan, Tianhong Dai, Wei Li, Zhan Lu, Hengyan Liu, Peian Huang, Guangyu Ren, Yonglin Luo, Chang Liu, Qiang Tu, Fangya Li, Ruipeng Gang, Chenghua Li, Jinjing Li, Sai Ma, Chenming Liu, Yizhen Cao, Steven Tel, Barthelemy Heyrman, Dominique Ginhac, Chul Lee, Gahyeon Kim, Seonghyun Park, An Gia Vien, Truong Thanh Nhat Mai, Howoon Yoon, Tu Vo, Alexander Holston, Sheir Zaheer, Chan Y. Park
The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).
1 code implementation • 12 May 2022 • Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Jinjin Gu, Yu Qiao, Chao Dong
One is the usage of blueprint separable convolution (BSConv), which takes place of the redundant convolution operation.
2 code implementations • 11 May 2022 • Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang
The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.
2 code implementations • CVPR 2023 • Xiangyu Chen, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong
In the training stage, we additionally adopt a same-task pre-training strategy to exploit the potential of the model for further improvement.
Ranked #1 on Image Super-Resolution on Set5 - 2x upscaling
1 code implementation • ICLR 2022 • Yurong You, Katie Z Luo, Xiangyu Chen, Junan Chen, Wei-Lun Chao, Wen Sun, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger
Self-driving cars must detect vehicles, pedestrians, and other traffic participants accurately to operate safely.
no code implementations • 11 Mar 2022 • Lin Liu, Lingxi Xie, Xiaopeng Zhang, Shanxin Yuan, Xiangyu Chen, Wengang Zhou, Houqiang Li, Qi Tian
In this paper, we propose a novel approach that embeds a task-agnostic prior into a transformer.
1 code implementation • 1 Feb 2022 • Xi Mo, Xiangyu Chen, Cuncong Zhong, Rui Li, Kaidong Li, Usman Sajid
Mean field approximation methodology has laid the foundation of modern Continuous Random Field (CRF) based solutions for the refinement of semantic segmentation.
2 code implementations • 24 Dec 2021 • Xi Mo, Xiangyu Chen
In this paper, we proposed an end-to-end realtime global attention neural network (RGANet) for the challenging task of semantic segmentation.
1 code implementation • ICLR 2022 • Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, Kilian Q Weinberger
Recent attempts at image steganography make use of advances in deep learning to train an encoder-decoder network pair to hide and retrieve secret messages in images.
no code implementations • 4 Sep 2021 • Usman Sajid, Xiangyu Chen, Hasan Sajid, Taejoon Kim, Guanghui Wang
Crowd estimation is a very challenging problem.
1 code implementation • ICCV 2021 • Xiangyu Chen, Zhengwen Zhang, Jimmy S. Ren, Lynhoo Tian, Yu Qiao, Chao Dong
However, most available resources are still in standard dynamic range (SDR).
1 code implementation • 15 Jun 2021 • Xiangyu Chen, Min Ye
In the same paper, a list decoding procedure was also introduced for two widely used classes of cyclic codes -- BCH codes and punctured Reed-Muller (RM) codes.
1 code implementation • 27 May 2021 • Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao, Chao Dong
In this work, we propose a novel learning-based approach using a spatially dynamic encoder-decoder network, HDRUNet, to learn an end-to-end mapping for single image HDR reconstruction with denoising and dequantization.
1 code implementation • 12 May 2021 • Xiangyu Chen, Min Ye
Finally, we propose a list decoding procedure that can significantly reduce the decoding error probability for BCH codes and punctured RM codes.
1 code implementation • 11 May 2021 • Xiangyu Chen, Guanghui Wang
We employ Discrete Cosine Transformation (DCT) to generate the frequency representation, then, integrate the features from both the spatial domain and frequency domain for classification.
no code implementations • 13 Apr 2021 • Yihao Liu, Jingwen He, Xiangyu Chen, Zhengwen Zhang, Hengyuan Zhao, Chao Dong, Yu Qiao
In practice, photo retouching can be accomplished by a series of image processing operations.
no code implementations • 5 Mar 2021 • Wankai Tang, Xiangyu Chen, Ming Zheng Chen, Jun Yan Dai, Yu Han, Shi Jin, Qiang Cheng, Geoffrey Ye Li, Tie Jun Cui
Channel reciprocity greatly facilitates downlink precoding in time-division duplexing (TDD) multiple-input multiple-output (MIMO) communications without the need for channel state information (CSI) feedback.
Information Theory Information Theory
no code implementations • 26 Feb 2021 • Johan Bjorck, Xiangyu Chen, Christopher De Sa, Carla P. Gomes, Kilian Q. Weinberger
Low-precision training has become a popular approach to reduce compute requirements, memory footprint, and energy consumption in supervised learning.
no code implementations • 21 Jan 2021 • Wankai Tang, Xiangyu Chen, Ming Zheng Chen, Jun Yan Dai, Yu Han, Marco Di Renzo, Shi Jin, Qiang Cheng, Tie Jun Cui
The refined model gives more accurate estimates of the path loss of RISs comprised of unit cells with a deep sub-wavelength size.
no code implementations • 28 Nov 2020 • Zhe Chu, Mengkai Hu, Xiangyu Chen
Recently, deep learning has been successfully applied to robotic grasp detection.
1 code implementation • CVPR 2020 • Yan Wang, Xiangyu Chen, Yurong You, Li Erran, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao
In the domain of autonomous driving, deep learning has substantially improved the 3D object detection accuracy for LiDAR and stereo camera data alike.
1 code implementation • 28 Apr 2020 • Xiangyu Chen, Zelin Ye, Jiankai Sun, Yuda Fan, Fang Hu, Chenxi Wang, Cewu Lu
Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects.
2 code implementations • CVPR 2020 • Hongxin Wei, Lei Feng, Xiangyu Chen, Bo An
The state-of-the-art approaches "Decoupling" and "Co-teaching+" claim that the "disagreement" strategy is crucial for alleviating the problem of learning with noisy labels.
Ranked #10 on Learning with noisy labels on CIFAR-10N-Random3
no code implementations • 13 Nov 2019 • Wankai Tang, Ming Zheng Chen, Xiangyu Chen, Jun Yan Dai, Yu Han, Marco Di Renzo, Yong Zeng, Shi Jin, Qiang Cheng, Tie Jun Cui
The measurement results match well with the modeling results, thus validating the proposed free-space path loss models for RIS, which may pave the way for further theoretical studies and practical applications in this field.
no code implementations • ICCV 2019 • Lu Zhang, Xiangyu Zhu, Xiangyu Chen, Xu Yang, Zhen Lei, Zhi-Yong Liu
In this paper, we propose a novel Aligned Region CNN (AR-CNN) to handle the weakly aligned multispectral data in an end-to-end way.
no code implementations • ICLR 2018 • Chen Wang, Xiangyu Chen, Zelin Ye, Jialu Wang, Ziruo Cai, Shixiang Gu, Cewu Lu
However, tasks with sparse rewards remain challenging when the state space is large.