5 code implementations • 24 Oct 2022 • Weihao Yu, Chenyang Si, Pan Zhou, Mi Luo, Yichen Zhou, Jiashi Feng, Shuicheng Yan, Xinchao Wang
By simply applying depthwise separable convolutions as token mixer in the bottom stages and vanilla self-attention in the top stages, the resulting model CAFormer sets a new record on ImageNet-1K: it achieves an accuracy of 85. 5% at 224x224 resolution, under normal supervised training without external data or distillation.
Ranked #57 on Image Classification on ImageNet (using extra training data)
no code implementations • 29 Aug 2022 • Shitong Sun, Chenyang Si, Shaogang Gong, Guile Wu
To resolve this problem, federated learning has been introduced to transfer knowledge across multiple sources (clients) with non-shared data while optimising a globally generalised central model (server).
2 code implementations • 25 May 2022 • Chenyang Si, Weihao Yu, Pan Zhou, Yichen Zhou, Xinchao Wang, Shuicheng Yan
Recent studies show that Transformer has strong capability of building long-range dependencies, yet is incompetent in capturing high frequencies that predominantly convey local information.
1 code implementation • 27 Mar 2022 • Pan Zhou, Yichen Zhou, Chenyang Si, Weihao Yu, Teck Khim Ng, Shuicheng Yan
It provides complementary instance supervision to IDS via an extra alignment on local neighbors, and scatters different local-groups separately to increase discriminability.
Ranked #2 on Self-Supervised Image Classification on ImageNet
Contrastive Learning Self-Supervised Image Classification +3
no code implementations • 1 Mar 2022 • Ke Han, Chenyang Si, Yan Huang, Liang Wang, Tieniu Tan
In this paper, we investigate the generalization problem of person re-identification (re-id), whose major challenge is the distribution shift on an unseen domain.
no code implementations • 22 Nov 2021 • Peng Wang, Jun Wen, Chenyang Si, Yuntao Qian, Liang Wang
Finally, in the Information Fuser, we explore varied strategies to combine the Sequence Reconstructor and Contrastive Motion Learner, and propose to capture postures and motions simultaneously via a knowledge-distillation based fusion strategy that transfers the motion learning from the Contrastive Motion Learner to the Sequence Reconstructor.
12 code implementations • CVPR 2022 • Weihao Yu, Mi Luo, Pan Zhou, Chenyang Si, Yichen Zhou, Xinchao Wang, Jiashi Feng, Shuicheng Yan
Based on this observation, we hypothesize that the general architecture of the Transformers, instead of the specific token mixer module, is more essential to the model's performance.
Ranked #9 on Semantic Segmentation on DensePASS
no code implementations • 25 May 2021 • Wentao Chen, Chenyang Si, Wei Wang, Liang Wang, Zilei Wang, Tieniu Tan
Few-shot learning is a challenging task since only few instances are given for recognizing an unseen class.
no code implementations • ECCV 2020 • Chenyang Si, Xuecheng Nie, Wei Wang, Liang Wang, Tieniu Tan, Jiashi Feng
Self-supervised learning (SSL) has been proved very effective at learning representations from unlabeled data in the image domain.
no code implementations • 10 Jun 2019 • Chenyang Si, Wentao Chen, Wei Wang, Liang Wang, Tieniu Tan
Furthermore, the inter-class classification and the intra-class transduction are extremely flexible to be repeated several times to progressively purify the clusters.
no code implementations • CVPR 2019 • Chenyang Si, Wentao Chen, Wei Wang, Liang Wang, Tieniu Tan
Nevertheless, how to effectively extract discriminative spatial and temporal features is still a challenging problem.
Ranked #40 on Skeleton Based Action Recognition on NTU RGB+D
no code implementations • 22 Sep 2018 • Ya Jing, Chenyang Si, Jun-Bo Wang, Wei Wang, Liang Wang, Tieniu Tan
To exploit the multilevel corresponding visual contents, we propose a pose-guided multi-granularity attention network (PMA).
no code implementations • CVPR 2018 • Chenyang Si, Wei Wang, Liang Wang, Tieniu Tan
Human image synthesis has extensive practical applications e. g. person re-identification and data augmentation for human pose estimation.
no code implementations • 22 May 2018 • Wei Wang, Jinjin Zhang, Chenyang Si, Liang Wang
Second, few pose-based methods model the action-related objects in recognizing human-object interaction actions in which objects play an important role.
Action Recognition In Videos Human-Object Interaction Detection +1
no code implementations • ECCV 2018 • Chenyang Si, Ya Jing, Wei Wang, Liang Wang, Tieniu Tan
Skeleton-based action recognition has made great progress recently, but many problems still remain unsolved.
Ranked #63 on Skeleton Based Action Recognition on NTU RGB+D