5 papers · 1 filter
MatLat: Material Latent Space for PBR Texture Generation
Kyeongmin Yeo, Yunhong Min, Jaihoon Kim +1
We propose a generative framework for producing high-quality PBR textures on a given 3D mesh. As large-scale PBR texture datasets are scarce, our approach focuses on effectively le…
StochSync: Stochastic Diffusion Synchronization for Image Generation in Arbitrary Spaces
Kyeongmin Yeo, Jaihoon Kim, Minhyuk Sung
We propose a zero-shot method for generating images in arbitrary spaces (e.g., a sphere for 360° panoramas and a mesh surface for texture) using a pretrained image diffusion model.…
ORIGEN: Zero-Shot 3D Orientation Grounding in Text-to-Image Generation
Yunhong Min, Daehyeon Choi, Kyeongmin Yeo +2
We introduce ORIGEN, the first zero-shot method for 3D orientation grounding in text-to-image generation across multiple objects and diverse categories. While previous work on spat…
Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses
Seungwoo Yoo, Juil Koo, Kyeongmin Yeo +1
We propose a novel method for learning representations of poses for 3D deformable objects, which specializes in 1) disentangling pose information from the object's identity, 2) fac…
SyncTweedies: A General Generative Framework Based on Synchronized Diffusions
Jaihoon Kim, Juil Koo, Kyeongmin Yeo +1
We introduce a general framework for generating diverse visual content, including ambiguous images, panorama images, mesh textures, and Gaussian splat textures, by synchronizing mu…