10 papers · 1 filter
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…
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…
DreamMakeup: Face Makeup Customization using Latent Diffusion Models
Geon Yeong Park, Inhwa Han, Serin Yang +7
The exponential growth of the global makeup market has paralleled advancements in virtual makeup simulation technology. Despite the progress led by GANs, their application still en…
Regularization by Texts for Latent Diffusion Inverse Solvers
Jeongsol Kim, Geon Yeong Park, Hyungjin Chung +1
The recent development of diffusion models has led to significant progress in solving inverse problems by leveraging these models as powerful generative priors. However, challenges…
Spectral Motion Alignment for Video Motion Transfer using Diffusion Models
Geon Yeong Park, Hyeonho Jeong, Sang Wan Lee +1
The evolution of diffusion models has greatly impacted video generation and understanding. Particularly, text-to-video diffusion models (VDMs) have significantly facilitated the cu…
Inference-Time Diffusion Model Distillation
Geon Yeong Park, Sang Wan Lee, Jong Chul Ye
Diffusion distillation models effectively accelerate reverse sampling by compressing the process into fewer steps. However, these models still exhibit a performance gap compared to…