2 papers
cs.CV2025
FreeCus: Free Lunch Subject-driven Customization in Diffusion Transformers
Yanbing Zhang, Zhe Wang, Qin Zhou +1
In light of recent breakthroughs in text-to-image (T2I) generation, particularly with diffusion transformers (DiT), subject-driven technologies are increasingly being employed for…
cs.CV2025
InstantCharacter: Personalize Any Characters with a Scalable Diffusion Transformer Framework
Jiale Tao, Yanbing Zhang, Qixun Wang +9
Current learning-based subject customization approaches, predominantly relying on U-Net architectures, suffer from limited generalization ability and compromised image quality. Mea…