activity
20212026
most citedNeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations

80 citations · 123 across the 19 of their papers we have counts for

collaborators

19 papers

cs.CV2026

ES3D: Embedding Semantics into 3D Space for Component-Aware Editing

Xuancheng Jin, Rengan Xie, Jiayuan Lu +5

Existing 3D editing methods have made notable progress in controllability, yet they remain limited in several important ways. Most approaches rely on text-driven editing, which str…

cs.SD2025

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…

cs.SD2025

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…

cs.CV2025

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…

cs.CV2025

EasyCraft: A Robust and Efficient Framework for Automatic Avatar Crafting

Suzhen Wang, Weijie Chen, Wei Zhang +5

Character customization, or 'face crafting,' is a vital feature in role-playing games (RPGs), enhancing player engagement by enabling the creation of personalized avatars. Existing…

cs.CV2024

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…

cs.CV2024★ 2 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.CV2023

Text-Guided 3D Face Synthesis -- From Generation to Editing

Yunjie Wu, Yapeng Meng, Zhipeng Hu +5

Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However, most existing works focus solely on the direct generation…

cs.CV2023★ 3 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★ 10 cited

EfficientDreamer: High-Fidelity and Robust 3D Creation via Orthogonal-view Diffusion Prior

Zhipeng Hu, Minda Zhao, Chaoyi Zhao +6

While image diffusion models have made significant progress in text-driven 3D content creation, they often fail to accurately capture the intended meaning of text prompts, especial…

cs.SD2023★ 2 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…

cs.CV2023★ 3 cited

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…

cs.CV2023★ 2 cited

DyGait: Exploiting Dynamic Representations for High-performance Gait Recognition

Ming Wang, Xianda Guo, Beibei Lin +5

Gait recognition is a biometric technology that recognizes the identity of humans through their walking patterns. Compared with other biometric technologies, gait recognition is mo…

cs.CV2023

NeFII: Inverse Rendering for Reflectance Decomposition with Near-Field Indirect Illumination

Haoqian Wu, Zhipeng Hu, Lincheng Li +3

Inverse rendering methods aim to estimate geometry, materials and illumination from multi-view RGB images. In order to achieve better decomposition, recent approaches attempt to mo…

cs.CV2022★ 21 cited

GaitGL: Learning Discriminative Global-Local Feature Representations for Gait Recognition

Beibei Lin, Shunli Zhang, Ming Wang +2

Existing gait recognition methods either directly establish Global Feature Representation (GFR) from original gait sequences or generate Local Feature Representation (LFR) from sev…

cs.CV2022★ 80 cited

NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations

Yunlong Ran, Jing Zeng, Shibo He +5

Implicit neural representations have shown compelling results in offline 3D reconstruction and also recently demonstrated the potential for online SLAM systems. However, applying t…

cs.CV2022

Learning Implicit Body Representations from Double Diffusion Based Neural Radiance Fields

Guangming Yao, Hongzhi Wu, Yi Yuan +3

In this paper, we present a novel double diffusion based neural radiance field, dubbed DD-NeRF, to reconstruct human body geometry and render the human body appearance in novel vie…

cs.CV2021

One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning

Suzhen Wang, Lincheng Li, Yu Ding +1

Audio-driven one-shot talking face generation methods are usually trained on video resources of various persons. However, their created videos often suffer unnatural mouth shapes a…