5 papers · 1 filter
"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…
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…
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…