most citedBag of Tricks and A Strong Baseline for Deep Person Re-identification

121 citations · 137 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Rethinking BiSeNet For Real-time Semantic Segmentation

Mingyuan Fan, Shenqi Lai, Junshi Huang +4

BiSeNet has been proved to be a popular two-stream network for real-time segmentation. However, its principle of adding an extra path to encode spatial information is time-consumin…

cs.CV202111 cited

Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition

Delian Ruan, Yan Yan, Shenqi Lai +3

In this paper, we propose a novel Feature Decomposition and Reconstruction Learning (FDRL) method for effective facial expression recognition. We view the expression information as…

cs.CV2019

Preparing Lessons: Improve Knowledge Distillation with Better Supervision

Tiancheng Wen, Shenqi Lai, Xueming Qian

Knowledge distillation (KD) is widely used for training a compact model with the supervision of another large model, which could effectively improve the performance. Previous metho…

cs.CV2019

A Strong Baseline and Batch Normalization Neck for Deep Person Re-identification

Hao Luo, Wei Jiang, Youzhi Gu +4

This study explores a simple but strong baseline for person re-identification (ReID). Person ReID with deep neural networks has progressed and achieved high performance in recent y…

cs.CV20195 cited

Grand Challenge of 106-Point Facial Landmark Localization

Yinglu Liu, Hao Shen, Yue Si +18

Facial landmark localization is a very crucial step in numerous face related applications, such as face recognition, facial pose estimation, face image synthesis, etc. However, pre…

cs.CV2019121 cited

Bag of Tricks and A Strong Baseline for Deep Person Re-identification

Hao Luo, Youzhi Gu, Xingyu Liao +2

This paper explores a simple and efficient baseline for person re-identification (ReID). Person re-identification (ReID) with deep neural networks has made progress and achieved hi…