2 citations · 2 across the 4 of their papers we have counts for
5 papers
VOR-Bench: A Human Perception-Driven Benchmark for Video Object Removal
Haonan Huang, Tianrui Qiu, Xianghao Zang +10
Despite its crucial role in video object removal (VOR), existing evaluation paradigms face two critical limitations: questionable references and a misalignment between tradi- tiona…
Curriculum Group Policy Optimization: Adaptive Sampling for Unleashing the Potential of Text-to-Image Generation
Baoteng Li, Xianghao Zang, Xinran Wang +8
Text-to-Image (T2I) generation has achieved remarkable progress in recent years. Meanwhile, reinforcement learning methods, particularly those based on Group Relative Policy Optimi…
Geometric Image Editing via Effects-Sensitive In-Context Inpainting with Diffusion Transformers
Shuo Zhang, Wenzhuo Wu, Huayu Zhang +8
Recent advances in diffusion models have significantly improved image editing. However, challenges persist in handling geometric transformations, such as translation, rotation, and…
FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models
Yuxuan Wang, Tianwei Cao, Huayu Zhang +3
Image generation has achieved remarkable progress with the development of large-scale text-to-image models, especially diffusion-based models. However, generating human images with…
OmniEraser: Remove Objects and Their Effects in Images with Paired Video-Frame Data
Runpu Wei, Zijin Yin, Shuo Zhang +8
Inpainting algorithms have achieved remarkable progress in removing objects from images, yet still face two challenges: 1) struggle to handle the object's visual effects such as sh…