no code implementations • ECCV 2020 • Tianjiao Li, Jun Liu, Wei zhang, Ling-Yu Duan
In this paper, we propose a novel Hardness-AwaRe Discrimination Network (HARD-Net) to specifically investigate the relationships between the similar activity pairs that are hard to be discriminated.
Ranked #6 on Skeleton Based Action Recognition on UAV-Human
1 code implementation • ECCV 2020 • Bin He, Ce Wang, Boxin Shi, Ling-Yu Duan
Frequency aliasing in the digital capture of display screens leads to the moir´e pattern, appearing as stripe-shaped distortions in images.
1 code implementation • ICCV 2023 • Xiaotong Li, Zixuan Hu, Yixiao Ge, Ying Shan, Ling-Yu Duan
The experimental results on 10 downstream tasks and 12 self-supervised models demonstrate that our approach can seamlessly integrate into existing ranking techniques and enhance their performances, revealing its effectiveness for the model selection task and its potential for understanding the mechanism in transfer learning.
1 code implementation • 16 Jan 2023 • Xiaotong Li, Zixuan Hu, Jun Liu, Yixiao Ge, Yongxing Dai, Ling-Yu Duan
In this paper, we improve the network generalization ability by modeling domain shifts with uncertainty (DSU), i. e., characterizing the feature statistics as uncertain distributions during training.
no code implementations • CVPR 2023 • Shengsen Wu, Yan Bai, Yihang Lou, Xiongkun Linghu, Jianzhong He, Ling-Yu Duan
Existing research mainly focuses on the one-to-one compatible paradigm, which is limited in learning compatibility among multiple models.
1 code implementation • 29 Mar 2022 • Xiaotong Li, Yixiao Ge, Kun Yi, Zixuan Hu, Ying Shan, Ling-Yu Duan
Image BERT pre-training with masked image modeling (MIM) becomes a popular practice to cope with self-supervised representation learning.
1 code implementation • CVPR 2022 • Lin Zhang, Li Shen, Liang Ding, DaCheng Tao, Ling-Yu Duan
Instead, we propose a data-free knowledge distillation method to fine-tune the global model in the server (FedFTG), which relieves the issue of direct model aggregation.
1 code implementation • 3 Mar 2022 • Yongxing Dai, Yifan Sun, Jun Liu, Zekun Tong, Yi Yang, Ling-Yu Duan
Instead of directly aligning the source and target domains against each other, we propose to align the source and target domains against their intermediate domains for a smooth knowledge transfer.
1 code implementation • ICLR 2022 • Xiaotong Li, Yongxing Dai, Yixiao Ge, Jun Liu, Ying Shan, Ling-Yu Duan
In this paper, we improve the network generalization ability by modeling the uncertainty of domain shifts with synthesized feature statistics during training.
no code implementations • 28 Dec 2021 • Haofeng Huang, Wenhan Yang, Yueyu Hu, Jiaying Liu, Ling-Yu Duan
In this paper, we make the first benchmark effort to elaborate on the superiority of using RAW images in the low light enhancement and develop a novel alternative route to utilize RAW images in a more flexible and practical way.
no code implementations • 18 Oct 2021 • Wenhan Yang, Haofeng Huang, Yueyu Hu, Ling-Yu Duan, Jiaying Liu
By keeping in mind the transferability among different machine vision tasks (e. g. high-level semantic and mid-level geometry-related), we aim to support multiple tasks jointly at low bit rates.
1 code implementation • 6 Aug 2021 • Yan Bai, Jile Jiao, Shengsen Wu, Yihang Lou, Jun Liu, Xuetao Feng, Ling-Yu Duan
It is a heavy workload to re-extract features of the whole database every time. Feature compatibility enables the learned new visual features to be directly compared with the old features stored in the database.
3 code implementations • ICCV 2021 • Yongxing Dai, Jun Liu, Yifan Sun, Zekun Tong, Chi Zhang, Ling-Yu Duan
To ensure these two properties to better characterize appropriate intermediate domains, we enforce the bridge losses on intermediate domains' prediction space and feature space, and enforce a diversity loss on the two domain factors.
Domain Adaptive Person Re-Identification Person Re-Identification
1 code implementation • CVPR 2021 • Qian Zheng, Boxin Shi, Jinnan Chen, Xudong Jiang, Ling-Yu Duan, Alex C. Kot
In this paper, we consider the absorption effect for the problem of single image reflection removal.
no code implementations • CVPR 2021 • Yan Bai, Jile Jiao, Wang Ce, Jun Liu, Yihang Lou, Xuetao Feng, Ling-Yu Duan
Recently, person re-identification (ReID) has vastly benefited from the surging waves of data-driven methods.
no code implementations • CVPR 2021 • Yongxing Dai, Xiaotong Li, Jun Liu, Zekun Tong, Ling-Yu Duan
Specifically, we propose a decorrelation loss to make the source domain networks (experts) keep the diversity and discriminability of individual domains' characteristics.
no code implementations • ICCV 2021 • Lin Zhang, Yong Luo, Yan Bai, Bo Du, Ling-Yu Duan
Federated Learning (FL) aims to establish a shared model across decentralized clients under the privacy-preserving constraint.
1 code implementation • 26 Dec 2020 • Yongxing Dai, Jun Liu, Yan Bai, Zekun Tong, Ling-Yu Duan
To this end, we propose a novel approach, called Dual-Refinement, that jointly refines pseudo labels at the off-line clustering phase and features at the on-line training phase, to alternatively boost the label purity and feature discriminability in the target domain for more reliable re-ID.
1 code implementation • 11 Dec 2020 • Wenjie Wang, Ling-Yu Duan, Hao Jiang, Peiguang Jing, Xuemeng Song, Liqiang Nie
With the rising incidence of some diseases, such as obesity and diabetes, a healthy diet is arousing increasing attention.
1 code implementation • ECCV 2020 • Haoran Wang, Tong Shen, Wei zhang, Ling-Yu Duan, Tao Mei
To fully exploit the supervision in the source domain, we propose a fine-grained adversarial learning strategy for class-level feature alignment while preserving the internal structure of semantics across domains.
Ranked #15 on Image-to-Image Translation on SYNTHIA-to-Cityscapes
no code implementations • 10 Jan 2020 • Ling-Yu Duan, Jiaying Liu, Wenhan Yang, Tiejun Huang, Wen Gao
Meanwhile, we systematically review state-of-the-art techniques in video compression and feature compression from the unique perspective of MPEG standardization, which provides the academic and industrial evidence to realize the collaborative compression of video and feature streams in a broad range of AI applications.
no code implementations • 9 Jan 2020 • Yueyu Hu, Shuai Yang, Wenhan Yang, Ling-Yu Duan, Jiaying Liu
In this paper, we come up with a novel image coding framework by leveraging both the compressive and the generative models, to support machine vision and human perception tasks jointly.
no code implementations • 9 Jan 2020 • Sifeng Xia, Kunchangtai Liang, Wenhan Yang, Ling-Yu Duan, Jiaying Liu
To this end, we make endeavors in leveraging the strength of predictive and generative models to support advanced compression techniques for both machine and human vision tasks simultaneously, in which visual features serve as a bridge to connect signal-level and task-level compact representations in a scalable manner.
1 code implementation • 31 Jul 2019 • Yihang Lou, Ling-Yu Duan, Yong Luo, Ziqian Chen, Tongliang Liu, Shiqi Wang, Wen Gao
The digital retina in smart cities is to select what the City Eye tells the City Brain, and convert the acquired visual data from front-end visual sensors to features in an intelligent sensing manner.
no code implementations • 25 Jul 2019 • Yun Ye, Yixin Li, Bo Wu, Wei zhang, Ling-Yu Duan, Tao Mei
For "hard" attributes with insufficient training data, Deact brings more stable synthetic samples for training and further improve the performance.
3 code implementations • 12 May 2019 • Jun Liu, Amir Shahroudy, Mauricio Perez, Gang Wang, Ling-Yu Duan, Alex C. Kot
Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition.
Ranked #5 on One-Shot 3D Action Recognition on NTU RGB+D 120
no code implementations • ICCV 2019 • Qian Zheng, Yiming Jia, Boxin Shi, Xudong Jiang, Ling-Yu Duan, Alex C. Kot
This paper solves the Sparse Photometric stereo through Lighting Interpolation and Normal Estimation using a generative Network (SPLINE-Net).
1 code implementation • CVPR 2019 • Qi Cai, Yingwei Pan, Chong-Wah Ngo, Xinmei Tian, Ling-Yu Duan, Ting Yao
The whole architecture is then optimized with three consistency regularizations: 1) region-level consistency to align the region-level predictions between teacher and student, 2) inter-graph consistency for matching the graph structures between teacher and student, and 3) intra-graph consistency to enhance the similarity between regions of same class within the graph of student.
1 code implementation • CVPR 2019 • Kean Chen, Jianguo Li, Weiyao Lin, John See, Ji Wang, Ling-Yu Duan, Zhibo Chen, Changwei He, Junni Zou
For this purpose, we develop a novel optimization algorithm, which seamlessly combines the error-driven update scheme in perceptron learning and backpropagation algorithm in deep networks.
no code implementations • 3 Mar 2019 • Renjie Wan, Boxin Shi, Haoliang Li, Ling-Yu Duan, Alex C. Kot
Face images captured through the glass are usually contaminated by reflections.
no code implementations • 8 Feb 2019 • Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot
Since there are significant temporal scale variations in the observed part of the ongoing action at different time steps, a novel window scale selection method is proposed to make our network focus on the performed part of the ongoing action and try to suppress the possible incoming interference from the previous actions at each step.
Ranked #64 on Skeleton Based Action Recognition on NTU RGB+D 120
no code implementations • 15 Jan 2019 • Jun Liu, Henghui Ding, Amir Shahroudy, Ling-Yu Duan, Xudong Jiang, Gang Wang, Alex C. Kot
Learning a set of features that are reliable and discriminatively representative of the pose of a hand (or body) part is difficult due to the ambiguities, texture and illumination variation, and self-occlusion in the real application of 3D pose estimation.
no code implementations • 9 Oct 2018 • Yong Luo, Yonggang Wen, Ling-Yu Duan, DaCheng Tao
Distance metric learning (DML) aims to find an appropriate way to reveal the underlying data relationship.
no code implementations • 17 Sep 2018 • Zhuo Chen, Weisi Lin, Shiqi Wang, Ling-Yu Duan, Alex C. Kot
The recent advances of hardware technology have made the intelligent analysis equipped at the front-end with deep learning more prevailing and practical.
no code implementations • CVPR 2018 • Jun Liu, Amir Shahroudy, Gang Wang, Ling-Yu Duan, Alex C. Kot
As there are significant temporal scale variations of the observed part of the ongoing action at different progress levels, we propose a novel window scale selection scheme to make our network focus on the performed part of the ongoing action and try to suppress the noise from the previous actions at each time step.
1 code implementation • CVPR 2018 • Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot
Removing the undesired reflections from images taken through the glass is of broad application to various computer vision tasks.
no code implementations • 5 Dec 2017 • Ling-Yu Duan, Yihang Lou, Shiqi Wang, Wen Gao, Yong Rui
To practically facilitate deep neural network models in the large-scale video analysis, there are still unprecedented challenges for the large-scale video data management.
no code implementations • ICCV 2017 • Renjie Wan, Boxin Shi, Ling-Yu Duan, Ah-Hwee Tan, Alex C. Kot
Removing undesired reflections from a photo taken in front of a glass is of great importance for enhancing the efficiency of visual computing systems.
no code implementations • 18 Jul 2017 • Jun Liu, Gang Wang, Ling-Yu Duan, Kamila Abdiyeva, Alex C. Kot
In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition.
Ranked #62 on Skeleton Based Action Recognition on NTU RGB+D 120
no code implementations • 18 Jul 2017 • Gaurav Manek, Jie Lin, Vijay Chandrasekhar, Ling-Yu Duan, Sateesh Giduthuri, Xiao-Li Li, Tomaso Poggio
In this work, we focus on the problem of image instance retrieval with deep descriptors extracted from pruned Convolutional Neural Networks (CNN).
no code implementations • CVPR 2017 • Jun Liu, Gang Wang, Ping Hu, Ling-Yu Duan, Alex C. Kot
Hence we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for 3D action recognition, which is able to selectively focus on the informative joints in the action sequence with the assistance of global contextual information.
Ranked #7 on One-Shot 3D Action Recognition on NTU RGB+D 120
no code implementations • 26 Apr 2017 • Ling-Yu Duan, Vijay Chandrasekhar, Shiqi Wang, Yihang Lou, Jie Lin, Yan Bai, Tiejun Huang, Alex ChiChung Kot, Wen Gao
This paper provides an overview of the on-going compact descriptors for video analysis standard (CDVA) from the ISO/IEC moving pictures experts group (MPEG).
no code implementations • 1 Mar 2017 • Feng Gao, Yihang Lou, Yan Bai, Shiqi Wang, Tiejun Huang, Ling-Yu Duan
Object detection aims to identify instances of semantic objects of a certain class in images or videos.
no code implementations • 1 Mar 2017 • Yan Bai, Feng Gao, Yihang Lou, Shiqi Wang, Tiejun Huang, Ling-Yu Duan
In this paper, we propose to leverage intra-class variance in metric learning of triplet network to improve the performance of fine-grained recognition.
no code implementations • 18 Jan 2017 • Vijay Chandrasekhar, Jie Lin, Qianli Liao, Olivier Morère, Antoine Veillard, Ling-Yu Duan, Tomaso Poggio
One major drawback of CNN-based {\it global descriptors} is that uncompressed deep neural network models require hundreds of megabytes of storage making them inconvenient to deploy in mobile applications or in custom hardware.