no code implementations • 2 May 2024 • Honglong Yang, Hui Tang, Xiaomeng Li
It has three novel designs: Image Feature Refiner (IFR), Text Feature Refiner (TFR) and Contrastive Aligner (CA).
2 code implementations • 25 Apr 2024 • Marcos V. Conde, Zhijun Lei, Wen Li, Cosmin Stejerean, Ioannis Katsavounidis, Radu Timofte, Kihwan Yoon, Ganzorig Gankhuyag, Jiangtao Lv, Long Sun, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Zhiyuan Li, Hao Wei, Chenyang Ge, Dongyang Zhang, Tianle Liu, Huaian Chen, Yi Jin, Menghan Zhou, Yiqiang Yan, Si Gao, Biao Wu, Shaoli Liu, Chengjian Zheng, Diankai Zhang, Ning Wang, Xintao Qiu, Yuanbo Zhou, Kongxian Wu, Xinwei Dai, Hui Tang, Wei Deng, Qingquan Gao, Tong Tong, Jae-Hyeon Lee, Ui-Jin Choi, Min Yan, Xin Liu, Qian Wang, Xiaoqian Ye, Zhan Du, Tiansen Zhang, Long Peng, Jiaming Guo, Xin Di, Bohao Liao, Zhibo Du, Peize Xia, Renjing Pei, Yang Wang, Yang Cao, ZhengJun Zha, Bingnan Han, Hongyuan Yu, Zhuoyuan Wu, Cheng Wan, Yuqing Liu, Haodong Yu, Jizhe Li, Zhijuan Huang, Yuan Huang, Yajun Zou, Xianyu Guan, Qi Jia, Heng Zhang, Xuanwu Yin, Kunlong Zuo, Hyeon-Cheol Moon, Tae-hyun Jeong, Yoonmo Yang, Jae-Gon Kim, Jinwoo Jeong, Sunjei Kim
This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolution (4x factor) in real-time on commercial GPUs.
3 code implementations • 22 Apr 2024 • Xiaoning Liu, Zongwei Wu, Ao Li, Florin-Alexandru Vasluianu, Yulun Zhang, Shuhang Gu, Le Zhang, Ce Zhu, Radu Timofte, Zhi Jin, Hongjun Wu, Chenxi Wang, Haitao Ling, Yuanhao Cai, Hao Bian, Yuxin Zheng, Jing Lin, Alan Yuille, Ben Shao, Jin Guo, Tianli Liu, Mohao Wu, Yixu Feng, Shuo Hou, Haotian Lin, Yu Zhu, Peng Wu, Wei Dong, Jinqiu Sun, Yanning Zhang, Qingsen Yan, Wenbin Zou, Weipeng Yang, Yunxiang Li, Qiaomu Wei, Tian Ye, Sixiang Chen, Zhao Zhang, Suiyi Zhao, Bo wang, Yan Luo, Zhichao Zuo, Mingshen Wang, Junhu Wang, Yanyan Wei, Xiaopeng Sun, Yu Gao, Jiancheng Huang, Hongming Chen, Xiang Chen, Hui Tang, Yuanbin Chen, Yuanbo Zhou, Xinwei Dai, Xintao Qiu, Wei Deng, Qinquan Gao, Tong Tong, Mingjia Li, Jin Hu, Xinyu He, Xiaojie Guo, sabarinathan, K Uma, A Sasithradevi, B Sathya Bama, S. Mohamed Mansoor Roomi, V. Srivatsav, Jinjuan Wang, Long Sun, Qiuying Chen, Jiahong Shao, Yizhi Zhang, Marcos V. Conde, Daniel Feijoo, Juan C. Benito, Alvaro García, Jaeho Lee, Seongwan Kim, Sharif S M A, Nodirkhuja Khujaev, Roman Tsoy, Ali Murtaza, Uswah Khairuddin, Ahmad 'Athif Mohd Faudzi, Sampada Malagi, Amogh Joshi, Nikhil Akalwadi, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudenagudi, Wenyi Lian, Wenjing Lian, Jagadeesh Kalyanshetti, Vijayalaxmi Ashok Aralikatti, Palani Yashaswini, Nitish Upasi, Dikshit Hegde, Ujwala Patil, Sujata C, Xingzhuo Yan, Wei Hao, Minghan Fu, Pooja Choksy, Anjali Sarvaiya, Kishor Upla, Kiran Raja, Hailong Yan, Yunkai Zhang, Baiang Li, Jingyi Zhang, Huan Zheng
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results.
no code implementations • 29 Mar 2024 • Hongzhi Liu, Guicheng Li, Jiacheng Nie, Hui Tang, Chunfeng Yang, Qianjin Feng, Hailin Xu, Yang Chen
Because of the complicated mechanism of ankle injury, it is very difficult to diagnose ankle fracture in clinic.
1 code implementation • 26 Mar 2024 • Yabin Zhang, Wenjie Zhu, Hui Tang, Zhiyuan Ma, Kaiyang Zhou, Lei Zhang
In this paper, we introduce a versatile adaptation approach that can effectively work under all three settings.
1 code implementation • 31 Aug 2023 • Yuanbin Chen, Tao Wang, Hui Tang, Longxuan Zhao, Ruige Zong, Shun Chen, Tao Tan, Xinlin Zhang, Tong Tong
In this paper, we present a novel semi-supervised learning method, Dual-Decoder Consistency via Pseudo-Labels Guided Data Augmentation (DCPA), for medical image segmentation.
1 code implementation • CVPR 2023 • Hui Tang, Kui Jia
Moreover, we use the simulation-to-reality adaptation as a downstream task for comparing the transferability between synthetic and real data when used for pre-training, which demonstrates that synthetic data pre-training is also promising to improve real test results.
1 code implementation • 14 Mar 2023 • Hui Tang, Yao Lu, Qi Xuan
Our SR-init method is inspired by the discovery that the accuracy drop due to stochastic re-initialization of layer parameters differs in various layers.
1 code implementation • 23 Feb 2023 • Hui Tang, YaoWei Wang, Kui Jia
Differently, motivated by the fundamental assumption for domain adaptability, we re-cast the domain adaptation problem as discriminative clustering of target data, given strong privileged information provided by the closely related, labeled source data.
no code implementations • 10 Mar 2022 • Hui Tang, Li Chai, Wanli Lu
To improve the recognition performance of the small micro-expression data, this paper presents a transferring dual stochastic Graph Convolutional Network (TDSGCN) model.
no code implementations • CVPR 2022 • Hui Tang, Kui Jia
To answer these problems, we propose a novel Taylor expansion inspired filtration (TEIF) framework, which admits the samples of moderate confidence with similar feature or gradient to the respective one averaged over the labeled and highly confident unlabeled data.
no code implementations • 28 Oct 2021 • Chenyu You, Lianyi Han, Aosong Feng, Ruihan Zhao, Hui Tang, Wei Fan
Space-time video super-resolution (STVSR) aims to construct a high space-time resolution video sequence from the corresponding low-frame-rate, low-resolution video sequence.
1 code implementation • 20 Aug 2021 • Longkun Zou, Hui Tang, Ke Chen, Kui Jia
The point cloud representation of an object can have a large geometric variation in view of inconsistent data acquisition procedure, which thus leads to domain discrepancy due to diverse and uncontrollable shape representation cross datasets.
1 code implementation • 14 Jun 2021 • Jingru Yi, Pengxiang Wu, Hui Tang, Bo Liu, Qiaoying Huang, Hui Qu, Lianyi Han, Wei Fan, Daniel J. Hoeppner, Dimitris N. Metaxas
To deal with this problem, in this paper, we propose an object-guided instance segmentation method.
1 code implementation • 10 Apr 2021 • Bin Deng, Yabin Zhang, Hui Tang, Changxing Ding, Kui Jia
The great promise that UB$^2$DA makes, however, brings significant learning challenges, since domain adaptation can only rely on the predictions of unlabeled target data in a partially overlapped label space, by accessing the interface of source model.
no code implementations • 10 Mar 2021 • Shao-jun Ji, Xiao-ming Zhou, Hui Tang, Hai-tao Wang, Jing-hui Zhang, Chun-hong qiao, Cheng-yu Fan
Cylindrical density depressions generated by femtosecond laser pulses filamenting in air for different energy depositions is investigated numerically, by using a set of hydrodynamic equations.
Optics Plasma Physics
1 code implementation • 5 Mar 2021 • Hui Tang, Kui Jia
Unsupervised domain adaptation aims to learn a task classifier that performs well on the unlabeled target domain, by utilizing the labeled source domain.
1 code implementation • ICCV 2021 • Longkun Zou, Hui Tang, Ke Chen, Kui Jia
The point cloud representation of an object can have a large geometric variation in view of inconsistent data acquisition procedure, which thus leads to domain discrepancy due to diverse and uncontrollable shape representation cross datasets.
2 code implementations • 8 Dec 2020 • Hui Tang, Xiatian Zhu, Ke Chen, Kui Jia, C. L. Philip Chen
To address this issue, we are motivated by a UDA assumption of structural similarity across domains, and propose to directly uncover the intrinsic target discrimination via constrained clustering, where we constrain the clustering solutions using structural source regularization that hinges on the very same assumption.
no code implementations • 28 May 2020 • Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang, Wei Fan, Kenneth M. C. Cheung, Michael To, Zhen Qian, Demetri Terzopoulos
Scoliosis is a congenital disease that causes lateral curvature in the spine.
no code implementations • 5 May 2020 • Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang, Wei Fan, Yuan Xiao, Dingjun Hao, Zhen Qian, Demetri Terzopoulos
Leveraging self-supervision and adversarial training, we propose a novel general purpose semi-supervised, multiple-task model---namely, self-supervised, semi-supervised, multitask learning (S$^4$MTL)---for accomplishing two important tasks in medical imaging, segmentation and diagnostic classification.
no code implementations • 15 Apr 2020 • Abdullah-Al-Zubaer Imran, Chao Huang, Hui Tang, Wei Fan, Kenneth M. C. Cheung, Michael To, Zhen Qian, Demetri Terzopoulos
Leveraging a carefully-adjusted U-Net model with progressive side outputs, we propose an end-to-end segmentation model that provides a fully automatic and reliable segmentation of the vertebrae associated with scoliosis measurement.
2 code implementations • CVPR 2020 • Hui Tang, Ke Chen, Kui Jia
To alleviate this risk, we are motivated by the assumption of structural domain similarity, and propose to directly uncover the intrinsic target discrimination via discriminative clustering of target data.
2 code implementations • 20 Feb 2020 • Yabin Zhang, Bin Deng, Hui Tang, Lei Zhang, Kui Jia
By using MCSD as a measure of domain distance, we develop a new domain adaptation bound for multi-class UDA; its data-dependent, probably approximately correct bound is also developed that naturally suggests adversarial learning objectives to align conditional feature distributions across source and target domains.
no code implementations • 9 Dec 2019 • Yuan Xue, Hui Tang, Zhi Qiao, Guanzhong Gong, Yong Yin, Zhen Qian, Chao Huang, Wei Fan, Xiaolei Huang
In this work, we propose to resolve the issue existing in current deep learning based organ segmentation systems that they often produce results that do not capture the overall shape of the target organ and often lack smoothness.
2 code implementations • 27 Nov 2019 • Hui Tang, Kui Jia
Based on an integrated category and domain classifier, DADA has a novel adversarial objective that encourages a mutually inhibitory relation between category and domain predictions for any input instance.
Ranked #1 on Synthetic-to-Real Translation on Syn2Real-C
no code implementations • 20 Nov 2019 • Jingru Yi, Hui Tang, Pengxiang Wu, Bo Liu, Daniel J. Hoeppner, Dimitris N. Metaxas, Lianyi Han, Wei Fan
Along with the instance normalization, the model is able to recover the target object distribution and suppress the distribution of neighboring attached objects.
1 code implementation • CVPR 2019 • Yabin Zhang, Hui Tang, Kui Jia, Mingkui Tan
Since target samples are unlabeled, we also propose a scheme of cross-domain training to help learn the target classifier.
no code implementations • 25 Nov 2018 • Liangjian Chen, Shih-Yao Lin, Yusheng Xie, Hui Tang, Yufan Xue, Xiaohui Xie, Yen-Yu Lin, Wei Fan
Hand pose estimation from a monocular RGB image is an important but challenging task.
1 code implementation • 31 Aug 2018 • Ken C. L. Wong, Mehdi Moradi, Hui Tang, Tanveer Syeda-Mahmood
In this paper, we propose a network architecture and the corresponding loss function which improve segmentation of very small structures.
2 code implementations • ECCV 2018 • Yabin Zhang, Hui Tang, Kui Jia
Fine-grained visual categorization (FGVC) is challenging due in part to the fact that it is often difficult to acquire an enough number of training samples.