activity
20212024
most citedGaitGL: Learning Discriminative Global-Local Feature Representations for Gait Recognition

21 citations · 41 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV20242 cited

Affective Behaviour Analysis via Integrating Multi-Modal Knowledge

Wei Zhang, Feng Qiu, Chen Liu +4

Affective Behavior Analysis aims to facilitate technology emotionally smart, creating a world where devices can understand and react to our emotions as humans do. To comprehensivel…

cs.CV20238 cited

High-Quality 3D Face Reconstruction with Affine Convolutional Networks

Zhiqian Lin, Jiangke Lin, Lincheng Li +2

Recent works based on convolutional encoder-decoder architecture and 3DMM parameterization have shown great potential for canonical view reconstruction from a single input image. C…

cs.CV20233 cited

CBARF: Cascaded Bundle-Adjusting Neural Radiance Fields from Imperfect Camera Poses

Hongyu Fu, Xin Yu, Lincheng Li +1

Existing volumetric neural rendering techniques, such as Neural Radiance Fields (NeRF), face limitations in synthesizing high-quality novel views when the camera poses of input ima…

cs.CV2023

BAVS: Bootstrapping Audio-Visual Segmentation by Integrating Foundation Knowledge

Chen Liu, Peike Li, Hu Zhang +4

Given an audio-visual pair, audio-visual segmentation (AVS) aims to locate sounding sources by predicting pixel-wise maps. Previous methods assume that each sound component in an a…

cs.CV2023

Zero-shot Text-driven Physically Interpretable Face Editing

Yapeng Meng, Songru Yang, Xu Hu +4

This paper proposes a novel and physically interpretable method for face editing based on arbitrary text prompts. Different from previous GAN-inversion-based face editing methods t…

cs.SD20232 cited

Audio-Visual Segmentation by Exploring Cross-Modal Mutual Semantics

Chen Liu, Peike Li, Xingqun Qi +4

The audio-visual segmentation (AVS) task aims to segment sounding objects from a given video. Existing works mainly focus on fusing audio and visual features of a given video to ac…