4 papers
HumanRefiner: Benchmarking Abnormal Human Generation and Refining with Coarse-to-fine Pose-Reversible Guidance
Guian Fang, Wenbiao Yan, Yuanfan Guo +5
Text-to-image diffusion models have significantly advanced in conditional image generation. However, these models usually struggle with accurately rendering images featuring humans…
Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution
Qingping Zheng, Ling Zheng, Yuanfan Guo +4
Artifact-free super-resolution (SR) aims to translate low-resolution images into their high-resolution counterparts with a strict integrity of the original content, eliminating any…
PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion
Guansong Lu, Yuanfan Guo, Jianhua Han +7
Current large-scale diffusion models represent a giant leap forward in conditional image synthesis, capable of interpreting diverse cues like text, human poses, and edges. However,…
Any-Size-Diffusion: Toward Efficient Text-Driven Synthesis for Any-Size HD Images
Qingping Zheng, Yuanfan Guo, Jiankang Deng +4
Stable diffusion, a generative model used in text-to-image synthesis, frequently encounters resolution-induced composition problems when generating images of varying sizes. This is…