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UniGP: Taming Diffusion Transformer for Prior-Preserved Unified Generation and Perception

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Recent advances in diffusion models have shown impressive performance in controllable image generation and dense prediction tasks. However, existing approaches typically treat diffusion-based controllable generation and dense prediction as separate tasks, overlooking the potential benefits of jointly modeling the heterogeneous distributions.

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arXiv AI
Jul 1

Histogram-constrained Image Generation

arXiv:2606. 31683v1 Announce Type: cross Abstract: Diffusion models have emerged as a dominant paradigm in generative modeling, enabling high-fidelity sampling from complex data distributions.

By Haoming Liu, Yuanhe Guo, Yijia Cao, Shenji Wan, Hongyi Wen