736 citations · 1.2k across the 40 of their papers we have counts for
10 papers · 1 filter
One for More: Selecting Generalizable Samples for Generalizable ReID Model
Enwei Zhang, Xinyang Jiang, Hao Cheng +7
Current training objectives of existing person Re-IDentification (ReID) models only ensure that the loss of the model decreases on selected training batch, with no regards to the p…
Learning with Instance-Dependent Label Noise: A Sample Sieve Approach
Hao Cheng, Zhaowei Zhu, Xingyu Li +3
Human-annotated labels are often prone to noise, and the presence of such noise will degrade the performance of the resulting deep neural network (DNN) models. Much of the literatu…
Pruning Filter in Filter
Fanxu Meng, Hao Cheng, Ke Li +4
Pruning has become a very powerful and effective technique to compress and accelerate modern neural networks. Existing pruning methods can be grouped into two categories: filter pr…
Removing the Background by Adding the Background: Towards Background Robust Self-supervised Video Representation Learning
Jinpeng Wang, Yuting Gao, Ke Li +7
Self-supervised learning has shown great potentials in improving the video representation ability of deep neural networks by getting supervision from the data itself. However, some…
Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion
Jinpeng Wang, Yuting Gao, Ke Li +5
One significant factor we expect the video representation learning to capture, especially in contrast with the image representation learning, is the object motion. However, we foun…
Devil's in the Details: Aligning Visual Clues for Conditional Embedding in Person Re-Identification
Fufu Yu, Xinyang Jiang, Yifei Gong +5
Although Person Re-Identification has made impressive progress, difficult cases like occlusion, change of view-pointand similar clothing still bring great challenges. Besides overa…