38 citations · 38 across the 9 of their papers we have counts for
6 papers · 1 filter
NeuralRemaster: Phase-Preserving Diffusion for Structure-Aligned Generation
Yu Zeng, Charles Ochoa, Mingyuan Zhou +3
Standard diffusion corrupts data using Gaussian noise whose Fourier coefficients have random magnitudes and random phases. While effective for unconditional or text-to-image genera…
"PhyWorldBench": A Comprehensive Evaluation of Physical Realism in Text-to-Video Models
Jing Gu, Xian Liu, Yu Zeng +8
Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurately simulate physical phenomena remains…
HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion
Yu Zeng, Yang Zhang, Jiachen Liu +4
Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using text descriptions or reference images, while preserving irrelevant attributes (e.g.…
JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation
Yu Zeng, Vishal M. Patel, Haochen Wang +4
Personalized text-to-image generation models enable users to create images that depict their individual possessions in diverse scenes, finding applications in various domains. To a…
Holo-Relighting: Controllable Volumetric Portrait Relighting from a Single Image
Yiqun Mei, Yu Zeng, He Zhang +6
At the core of portrait photography is the search for ideal lighting and viewpoint. The process often requires advanced knowledge in photography and an elaborate studio setup. In t…
Fast Learning Radiance Fields by Shooting Much Fewer Rays
Wenyuan Zhang, Ruofan Xing, Yunfan Zeng +3
Learning radiance fields has shown remarkable results for novel view synthesis. The learning procedure usually costs lots of time, which motivates the latest methods to speed up th…