8 papers · 1 filter
RelightFormer: Feed-forward Generative Transformer for Multiview Object Relighting
Hejun Wang, Jinxi Li, Junwei Jiang +4
Image relighting is traditionally tackled via complex inverse rendering pipelines, which suffer from ill-posed optimization, or single-image generative models that ignore crucial m…
PhysInOne: Visual Physics Learning and Reasoning in One Suite
Siyuan Zhou, Hejun Wang, Hu Cheng +36
We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike existing datasets limited to mere…
Improving Multi-View Reconstruction via Texture-Guided Gaussian-Mesh Joint Optimization
Zhejia Cai, Puhua Jiang, Shiwei Mao +2
Reconstructing real-world objects from multi-view images is essential for applications in 3D editing, AR/VR, and digital content creation. Existing methods typically prioritize eit…
Auto-Connect: Connectivity-Preserving RigFormer with Direct Preference Optimization
Jingfeng Guo, Jian Liu, Jinnan Chen +9
We introduce Auto-Connect, a novel approach for automatic rigging that explicitly preserves skeletal connectivity through a connectivity-preserving tokenization scheme. Unlike prev…
ARMO: Autoregressive Rigging for Multi-Category Objects
Mingze Sun, Shiwei Mao, Keyi Chen +5
Recent advancements in large-scale generative models have significantly improved the quality and diversity of 3D shape generation. However, most existing methods focus primarily on…
DRiVE: Diffusion-based Rigging Empowers Generation of Versatile and Expressive Characters
Mingze Sun, Junhao Chen, Junting Dong +7
Recent advances in generative models have enabled high-quality 3D character reconstruction from multi-modal. However, animating these generated characters remains a challenging tas…