24 citations · 30 across the 8 of their papers we have counts for
Showing 2024 · cs.CVShow all
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cs.CV2024
Training-free Regional Prompting for Diffusion Transformers
Anthony Chen, Jianjin Xu, Wenzhao Zheng +5
Diffusion models have demonstrated excellent capabilities in text-to-image generation. Their semantic understanding (i.e., prompt following) ability has also been greatly improved…
cs.CV2024★ 5 cited
InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation
Haofan Wang, Matteo Spinelli, Qixun Wang +3
Tuning-free diffusion-based models have demonstrated significant potential in the realm of image personalization and customization. However, despite this notable progress, current…
cs.CV2024★ 24 cited
InstantID: Zero-shot Identity-Preserving Generation in Seconds
Qixun Wang, Xu Bai, Haofan Wang +5
There has been significant progress in personalized image synthesis with methods such as Textual Inversion, DreamBooth, and LoRA. Yet, their real-world applicability is hindered by…