1 citations · 1 across the 14 of their papers we have counts for
5 papers · 2 filters
4Real-Video: Learning Generalizable Photo-Realistic 4D Video Diffusion
Chaoyang Wang, Peiye Zhuang, Tuan Duc Ngo +7
We propose 4Real-Video, a novel framework for generating 4D videos, organized as a grid of video frames with both time and viewpoint axes. In this grid, each row contains frames sh…
VD3D: Taming Large Video Diffusion Transformers for 3D Camera Control
Sherwin Bahmani, Ivan Skorokhodov, Aliaksandr Siarohin +9
Modern text-to-video synthesis models demonstrate coherent, photorealistic generation of complex videos from a text description. However, most existing models lack fine-grained con…
GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement
Peiye Zhuang, Songfang Han, Chaoyang Wang +7
We propose a novel approach for 3D mesh reconstruction from multi-view images. Our method takes inspiration from large reconstruction models like LRM that use a transformer-based t…
SPAD : Spatially Aware Multiview Diffusers
Yash Kant, Ziyi Wu, Michael Vasilkovsky +7
We present SPAD, a novel approach for creating consistent multi-view images from text prompts or single images. To enable multi-view generation, we repurpose a pretrained 2D diffus…
AToM: Amortized Text-to-Mesh using 2D Diffusion
Guocheng Qian, Junli Cao, Aliaksandr Siarohin +12
We introduce Amortized Text-to-Mesh (AToM), a feed-forward text-to-mesh framework optimized across multiple text prompts simultaneously. In contrast to existing text-to-3D methods…