7 papers
RigMo: Unifying Rig and Motion Learning for Generative Animation
Hao Zhang, Jiahao Luo, Bohui Wan +7
Despite significant progress in 4D generation, rig and motion, the core structural and dynamic components of animation are typically modeled as separate problems. Existing pipeline…
RGB-Only Supervised Camera Parameter Optimization in Dynamic Scenes
Fang Li, Hao Zhang, Narendra Ahuja
Although COLMAP has long remained the predominant method for camera parameter optimization in static scenes, it is constrained by its lengthy runtime and reliance on ground truth (…
Stable Part Diffusion 4D: Multi-View RGB and Kinematic Parts Video Generation
Hao Zhang, Chun-Han Yao, Simon Donné +2
We present Stable Part Diffusion 4D (SP4D), a framework for generating paired RGB and kinematic part videos from monocular inputs. Unlike conventional part segmentation methods tha…
PhysRig: Differentiable Physics-Based Skinning and Rigging Framework for Realistic Articulated Object Modeling
Hao Zhang, Haolan Xu, Chun Feng +2
Skinning and rigging are fundamental components in animation, articulated object reconstruction, motion transfer, and 4D generation. Existing approaches predominantly rely on Linea…
Measuring the (Un)Faithfulness of Concept-Based Explanations
Shubham Kumar, Narendra Ahuja
Deep vision models perform input-output computations that are hard to interpret. Concept-based explanation methods (CBEMs) increase interpretability by re-expressing parts of the m…
Efficiently Disentangling CLIP for Multi-Object Perception
Samyak Rawlekar, Yujun Cai, Yiwei Wang +2
Vision-language models like CLIP excel at recognizing the single, prominent object in a scene. However, they struggle in complex scenes containing multiple objects. We identify a f…