13 citations · 30 across the 19 of their papers we have counts for
4 papers · 1 filter
SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priors
Dave Zhenyu Chen, Haoxuan Li, Hsin-Ying Lee +2
We propose SceneTex, a novel method for effectively generating high-quality and style-consistent textures for indoor scenes using depth-to-image diffusion priors. Unlike previous m…
Generating Context-Aware Natural Answers for Questions in 3D Scenes
Mohammed Munzer Dwedari, Matthias Niessner, Dave Zhenyu Chen
3D question answering is a young field in 3D vision-language that is yet to be explored. Previous methods are limited to a pre-defined answer space and cannot generate answers natu…
Prompt Switch: Efficient CLIP Adaptation for Text-Video Retrieval
Chaorui Deng, Qi Chen, Pengda Qin +2
In text-video retrieval, recent works have benefited from the powerful learning capabilities of pre-trained text-image foundation models (e.g., CLIP) by adapting them to the video…
Text2Tex: Text-driven Texture Synthesis via Diffusion Models
Dave Zhenyu Chen, Yawar Siddiqui, Hsin-Ying Lee +2
We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-awar…