activity
20172026
most citedLearning Multi-Attention Context Graph for Group-Based Re-Identification

73 citations · 184 across the 49 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

cs.CV2025

POLAR: A Portrait OLAT Dataset and Generative Framework for Illumination-Aware Face Modeling

Zhuo Chen, Chengqun Yang, Zhuo Su +5

Face relighting aims to synthesize realistic portraits under novel illumination while preserving identity and geometry. However, progress remains constrained by the limited availab…

cs.CV2025

MoRE: 3D Visual Geometry Reconstruction Meets Mixture-of-Experts

Jingnan Gao, Zhe Wang, Xianze Fang +7

Recent advances in language and vision have demonstrated that scaling up model capacity consistently improves performance across diverse tasks. In 3D visual geometry reconstruction…

cs.CV2025

Perceiving and Acting in First-Person: A Dataset and Benchmark for Egocentric Human-Object-Human Interactions

Liang Xu, Chengqun Yang, Zili Lin +11

Learning action models from real-world human-centric interaction datasets is important towards building general-purpose intelligent assistants with efficiency. However, most existi…

cs.CV2025★ 1 cited

Dens3R: A Foundation Model for 3D Geometry Prediction

Xianze Fang, Jingnan Gao, Zhe Wang +8

Recent advances in dense 3D reconstruction have led to significant progress, yet achieving accurate unified geometric prediction remains a major challenge. Most existing methods ar…

cs.CV2025

Towards High-fidelity 3D Talking Avatar with Personalized Dynamic Texture

Xuanchen Li, Jianyu Wang, Yuhao Cheng +5

Significant progress has been made for speech-driven 3D face animation, but most works focus on learning the motion of mesh/geometry, ignoring the impact of dynamic texture. In thi…

cs.CV2025★ 1 cited

MARS: Mesh AutoRegressive Model for 3D Shape Detailization

Jingnan Gao, Weizhe Liu, Weixuan Sun +8

State-of-the-art methods for mesh detailization predominantly utilize Generative Adversarial Networks (GANs) to generate detailed meshes from coarse ones. These methods typically l…