4 papers
STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer
Yushi Lan, Yihang Luo, Fangzhou Hong +7
We present STream3R, a novel approach to 3D reconstruction that reformulates pointmap prediction as a decoder-only Transformer problem. Existing state-of-the-art methods for multi-…
GaussianAnything: Interactive Point Cloud Flow Matching For 3D Object Generation
Yushi Lan, Shangchen Zhou, Zhaoyang Lyu +5
While 3D content generation has advanced significantly, existing methods still face challenges with input formats, latent space design, and output representations. This paper intro…
LN3DIFF++: Scalable Latent Neural Fields Diffusion for Speedy 3D Generation
Yushi Lan, Fangzhou Hong, Shangchen Zhou +7
The field of neural rendering has witnessed significant progress with advancements in generative models and differentiable rendering techniques. Though 2D diffusion has achieved su…
DiffMorpher: Unleashing the Capability of Diffusion Models for Image Morphing
Kaiwen Zhang, Yifan Zhou, Xudong Xu +2
Diffusion models have achieved remarkable image generation quality surpassing previous generative models. However, a notable limitation of diffusion models, in comparison to GANs,…