9 papers · 1 filter
MeshReGen: A Unified 3D Geometry Regeneration Framework
Geon Yeong Park, Roman Shapovalov, Rakesh Ranjan +3
We consider the problem of regenerating 3D objects from 2D images and initial 3D shapes. Most 3D generators operate in a one-shot fashion, converting text or images to a 3D object…
Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing
Dohun Lee, Chun-Hao Paul Huang, Xuelin Chen +3
Video-to-video diffusion models achieve impressive single-turn editing performance, but practical editing workflows are inherently iterative. When edits are applied sequentially, e…
Zero4D: Training-Free 4D Video Generation From Single Video Using Off-the-Shelf Video Diffusion
Jangho Park, Taesung Kwon, Jong Chul Ye
Multi-view or 4D video generation has emerged as a significant research topic. Nonetheless, recent approaches to 4D generation still struggle with fundamental limitations, as they…
VISION-XL: High Definition Video Inverse Problem Solver using Latent Image Diffusion Models
Taesung Kwon, Jong Chul Ye
In this paper, we propose a novel framework for solving high-definition video inverse problems using latent image diffusion models. Building on recent advancements in spatio-tempor…
TweedieMix: Improving Multi-Concept Fusion for Diffusion-based Image/Video Generation
Gihyun Kwon, Jong Chul Ye
Despite significant advancements in customizing text-to-image and video generation models, generating images and videos that effectively integrate multiple personalized concepts re…
ViBiDSampler: Enhancing Video Interpolation Using Bidirectional Diffusion Sampler
Serin Yang, Taesung Kwon, Jong Chul Ye
Recent progress in large-scale text-to-video (T2V) and image-to-video (I2V) diffusion models has greatly enhanced video generation, especially in terms of keyframe interpolation. H…