12 citations · 29 across the 10 of their papers we have counts for
10 papers
Discovering Influential Neuron Path in Vision Transformers
Yifan Wang, Yifei Liu, Yingdong Shi +5
Vision Transformer models exhibit immense power yet remain opaque to human understanding, posing challenges and risks for practical applications. While prior research has attempted…
Dissecting and Mitigating Diffusion Bias via Mechanistic Interpretability
Yingdong Shi, Changming Li, Yifan Wang +5
Diffusion models have demonstrated impressive capabilities in synthesizing diverse content. However, despite their high-quality outputs, these models often perpetuate social biases…
MVPaint: Synchronized Multi-View Diffusion for Painting Anything 3D
Wei Cheng, Juncheng Mu, Xianfang Zeng +8
Texturing is a crucial step in the 3D asset production workflow, which enhances the visual appeal and diversity of 3D assets. Despite recent advancements in Text-to-Texture (T2T) g…
MeshXL: Neural Coordinate Field for Generative 3D Foundation Models
Sijin Chen, Xin Chen, Anqi Pang +11
The polygon mesh representation of 3D data exhibits great flexibility, fast rendering speed, and storage efficiency, which is widely preferred in various applications. However, giv…
CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assets
Longwen Zhang, Ziyu Wang, Qixuan Zhang +6
In the realm of digital creativity, our potential to craft intricate 3D worlds from imagination is often hampered by the limitations of existing digital tools, which demand extensi…
Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions
Guoxing Sun, Xin Chen, Yizhang Chen +6
4D reconstruction of human-object interaction is critical for immersive VR/AR experience and human activity understanding. Recent advances still fail to recover fine geometry and t…
Few-shot Neural Human Performance Rendering from Sparse RGBD Videos
Anqi Pang, Xin Chen, Haimin Luo +3
Recent neural rendering approaches for human activities achieve remarkable view synthesis results, but still rely on dense input views or dense training with all the capture frames…
SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos
Xin Chen, Anqi Pang, Wei Yang +3
Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-…
ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal References
Yannan He, Anqi Pang, Xin Chen +4
Capturing challenging human motions is critical for numerous applications, but it suffers from complex motion patterns and severe self-occlusion under the monocular setting. In thi…
TightCap: 3D Human Shape Capture with Clothing Tightness Field
Xin Chen, Anqi Pang, Yang Wei +2
In this paper, we present TightCap, a data-driven scheme to capture both the human shape and dressed garments accurately with only a single 3D human scan, which enables numerous ap…