3 citations · 14 across the 13 of their papers we have counts for
13 papers
Robust Audio-Visual Segmentation via Audio-Guided Visual Convergent Alignment
Chen Liu, Peike Li, Liying Yang +3
Accurately localizing audible objects based on audio-visual cues is the core objective of audio-visual segmentation. Most previous methods emphasize spatial or temporal multi-modal…
Dynamic Derivation and Elimination: Audio Visual Segmentation with Enhanced Audio Semantics
Chen Liu, Liying Yang, Peike Li +3
Sound-guided object segmentation has drawn considerable attention for its potential to enhance multimodal perception. Previous methods primarily focus on developing advanced archit…
7ABAW-Compound Expression Recognition via Curriculum Learning
Chen Liu, Feng Qiu, Wei Zhang +3
With the advent of deep learning, expression recognition has made significant advancements. However, due to the limited availability of annotated compound expression datasets and t…
FreeAvatar: Robust 3D Facial Animation Transfer by Learning an Expression Foundation Model
Feng Qiu, Wei Zhang, Chen Liu +6
Video-driven 3D facial animation transfer aims to drive avatars to reproduce the expressions of actors. Existing methods have achieved remarkable results by constraining both geome…
Affective Behaviour Analysis via Progressive Learning
Chen Liu, Wei Zhang, Feng Qiu +2
Affective Behavior Analysis aims to develop emotionally intelligent technology that can recognize and respond to human emotions. To advance this field, the 7th Affective Behavior A…
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…
Divide and Ensemble: Progressively Learning for the Unknown
Hu Zhang, Xin Shen, Heming Du +10
In the wheat nutrient deficiencies classification challenge, we present the DividE and EnseMble (DEEM) method for progressive test data predictions. We find that (1) test images ar…
When 3D Bounding-Box Meets SAM: Point Cloud Instance Segmentation with Weak-and-Noisy Supervision
Qingtao Yu, Heming Du, Chen Liu +1
Learning from bounding-boxes annotations has shown great potential in weakly-supervised 3D point cloud instance segmentation. However, we observed that existing methods would suffe…
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…
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…
EmotionGesture: Audio-Driven Diverse Emotional Co-Speech 3D Gesture Generation
Xingqun Qi, Chen Liu, Lincheng Li +3
Generating vivid and diverse 3D co-speech gestures is crucial for various applications in animating virtual avatars. While most existing methods can generate gestures from audio di…
Diverse 3D Hand Gesture Prediction from Body Dynamics by Bilateral Hand Disentanglement
Xingqun Qi, Chen Liu, Muyi Sun +3
Predicting natural and diverse 3D hand gestures from the upper body dynamics is a practical yet challenging task in virtual avatar creation. Previous works usually overlook the asy…
Evidence-based Match-status-Aware Gait Recognition for Out-of-Gallery Gait Identification
Heming Du, Chen Liu, Ming Wang +3
Existing gait recognition methods typically identify individuals based on the similarity between probe and gallery samples. However, these methods often neglect the fact that the g…