collaborators

8 papers

cs.CV2026

FlowLong: Inference-time Long Video Generation via Manifold-constrained Tweedie Matching

Jangho Park, Geon Yeong Park, Gihyun Kwon +1

Extending the generation horizon of video diffusion models to long sequences remains a long-standing and important challenge. Existing training-free approaches fall into two catego…

cs.CV2026

Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models

Taesung Kwon, Jonghyun Park, Hyungjin Chung +1

Diffusion models provide powerful priors for zero-shot video inverse problems, but their real-time deployment is hindered by two inefficiencies: high initial latency caused by holi…

cs.CV2025

Improving Video Diffusion Transformer Training by Multi-Feature Fusion and Alignment from Self-Supervised Vision Encoders

Dohun Lee, Hyeonho Jeong, Jiwook Kim +2

Video diffusion models have advanced rapidly in the recent years as a result of series of architectural innovations (e.g., diffusion transformers) and use of novel training objecti…

cs.CV2025

Reangle-A-Video: 4D Video Generation as Video-to-Video Translation

Hyeonho Jeong, Suhyeon Lee, Jong Chul Ye

We introduce Reangle-A-Video, a unified framework for generating synchronized multi-view videos from a single input video. Unlike mainstream approaches that train multi-view video…

cs.CV2025

Generalized Consistency Trajectory Models for Image Manipulation

Beomsu Kim, Jaemin Kim, Jeongsol Kim +1

Diffusion models (DMs) excel in unconditional generation, as well as on applications such as image editing and restoration. The success of DMs lies in the iterative nature of diffu…

cs.LG2025

LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR Models

Jinho Chang, Jong Chul Ye

With the emergence of diffusion models as a frontline generative model, many researchers have proposed molecule generation techniques with conditional diffusion models. However, th…