3 citations · 3 across the 3 of their papers we have counts for
4 papers
FAMOS: Feed-Forward 3D Articulation Modeling from Sparse Observations
Kevin Qu, Tao Sun, Massimiliano Viola +5
Modeling articulated objects from sparse monocular views is challenging because each observation reveals only partial geometry and motion evidence. Most feed-forward methods infer…
Temporal Score Rescaling for Temperature Sampling in Diffusion and Flow Models
Yanbo Xu, Yu Wu, Sungjae Park +2
We present a mechanism to steer the sampling diversity of denoising diffusion and flow matching models, allowing users to sample from a sharper or broader distribution than the tra…
MVD-Fusion: Single-view 3D via Depth-consistent Multi-view Generation
Hanzhe Hu, Zhizhuo Zhou, Varun Jampani +1
We present MVD-Fusion: a method for single-view 3D inference via generative modeling of multi-view-consistent RGB-D images. While recent methods pursuing 3D inference advocate lear…
SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstruction
Zhizhuo Zhou, Shubham Tulsiani
We propose SparseFusion, a sparse view 3D reconstruction approach that unifies recent advances in neural rendering and probabilistic image generation. Existing approaches typically…