4 papers
Training-free image inversion for one-step diffusion models
Tao Wu, Senmao Li, Yaxing Wang +3
In this work, we introduce a novel training-free inversion (TFinv) framework for one-step diffusion models,addressing key challenges in real image inversion and editing. We first i…
Adversarial Concept Distillation for One-Step Diffusion Personalization
Yixiong Yang, Tao Wu, Senmao Li +4
Recent progress in accelerating text-to-image diffusion models enables high-fidelity synthesis within a single denoising step. However, customizing the fast one-step models remains…
GeodesicNVS: Probability Density Geodesic Flow Matching for Novel View Synthesis
Xuqin Wang, Tao Wu, Yanfeng Zhang +5
Recent advances in generative modeling have substantially enhanced novel view synthesis, yet maintaining consistency across viewpoints remains challenging. Diffusion-based models r…
GenColorBench: A Color Evaluation Benchmark for Text-to-Image Generation Models
Muhammad Atif Butt, Alexandra Gomez-Villa, Tao Wu +3
Recent years have seen impressive advances in text-to-image generation, with image generative or unified models producing high-quality images from text. Yet these models still stru…