most citedMulti-modal Multi-label Facial Action Unit Detection with Transformer

10 citations · 22 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202210 cited

Multi-modal Multi-label Facial Action Unit Detection with Transformer

Lingfeng Wang, Shisen Wang, Jin Qi

Facial Action Coding System is an important approach of facial expression analysis.This paper describes our submission to the third Affective Behavior Analysis (ABAW) 2022 competit…

eess.IV2021

TSN-CA: A Two-Stage Network with Channel Attention for Low-Light Image Enhancement

Xinxu Wei, Xianshi Zhang, Shisen Wang +2

Low-light image enhancement is a challenging low-level computer vision task because after we enhance the brightness of the image, we have to deal with amplified noise, color distor…

eess.IV20215 cited

DA-DRN: Degradation-Aware Deep Retinex Network for Low-Light Image Enhancement

Xinxu Wei, Xianshi Zhang, Shisen Wang +4

Images obtained in real-world low-light conditions are not only low in brightness, but they also suffer from many other types of degradation, such as color distortion, unknown nois…

cs.CV20214 cited

A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysis

Lingfeng Wang, Shisen Wang, Jin Qi +1

Affective Behavior Analysis is an important part in human-computer interaction. Existing multi-task affective behavior recognition methods suffer from the problem of incomplete lab…

eess.IV20213 cited

BLNet: A Fast Deep Learning Framework for Low-Light Image Enhancement with Noise Removal and Color Restoration

Xinxu Wei, Xianshi Zhang, Shisen Wang +4

Images obtained in real-world low-light conditions are not only low in brightness, but they also suffer from many other types of degradation, such as color bias, unknown noise, det…