activity
20172022
most citedNTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

1.8k citations · 3k across the 32 of their papers we have counts for

collaborators
Showing 2021Show all

7 papers · 1 filter

eess.IV2021★ 76 cited

Towards Low Light Enhancement with RAW Images

Haofeng Huang, Wenhan Yang, Yueyu Hu +2

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…

cs.CV2021★ 14 cited

Video Coding for Machine: Compact Visual Representation Compression for Intelligent Collaborative Analytics

Wenhan Yang, Haofeng Huang, Yueyu Hu +2

Video Coding for Machines (VCM) is committed to bridging to an extent separate research tracks of video/image compression and feature compression, and attempts to optimize compactn…

cs.CV2021

Dual-Tuning: Joint Prototype Transfer and Structure Regularization for Compatible Feature Learning

Yan Bai, Jile Jiao, Shengsen Wu +4

Visual retrieval system faces frequent model update and deployment. It is a heavy workload to re-extract features of the whole database every time.Feature compatibility enables the…

cs.CV2021★ 7 cited

IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID

Yongxing Dai, Jun Liu, Yifan Sun +3

Unsupervised domain adaptive person re-identification (UDA re-ID) aims at transferring the labeled source domain's knowledge to improve the model's discriminability on the unlabele…

cs.CV2021

Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation

Shengsen Wu, Liang Chen, Yihang Lou +4

In object re-identification (ReID), the development of deep learning techniques often involves model updates and deployment. It is unbearable to re-embedding and re-index with the…

cs.CV2021★ 11 cited

Generalizable Person Re-identification with Relevance-aware Mixture of Experts

Yongxing Dai, Xiaotong Li, Jun Liu +2

Domain generalizable (DG) person re-identification (ReID) is a challenging problem because we cannot access any unseen target domain data during training. Almost all the existing D…

cs.CV2021★ 12 cited

Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification

Yongxing Dai, Jun Liu, Yan Bai +2

Unsupervised domain adaptive (UDA) person re-identification (re-ID) is a challenging task due to the missing of labels for the target domain data. To handle this problem, some rece…