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RefineAnything: Multimodal Region-Specific Refinement for Perfect Local Details
Dewei Zhou, You Li, Zongxin Yang +1
We introduce region-specific image refinement as a dedicated problem setting: given an input image and a user-specified region (e.g., a scribble mask or a bounding box), the goal i…
BideDPO: Conditional Image Generation with Simultaneous Text and Condition Alignment
Dewei Zhou, Mingwei Li, Zongxin Yang +5
Conditional image generation enhances text-to-image synthesis with structural, spatial, or stylistic priors, but current methods face challenges in handling conflicts between sourc…
ContextGen: Contextual Layout Anchoring for Identity-Consistent Multi-Instance Generation
Ruihang Xu, Dewei Zhou, Fan Ma +1
Multi-instance image generation (MIG) remains a significant challenge for modern diffusion models due to key limitations in achieving precise control over object layout and preserv…
DreamRenderer: Taming Multi-Instance Attribute Control in Large-Scale Text-to-Image Models
Dewei Zhou, Mingwei Li, Zongxin Yang +1
Image-conditioned generation methods, such as depth- and canny-conditioned approaches, have demonstrated remarkable abilities for precise image synthesis. However, existing models…
3DIS-FLUX: simple and efficient multi-instance generation with DiT rendering
Dewei Zhou, Ji Xie, Zongxin Yang +1
The growing demand for controllable outputs in text-to-image generation has driven significant advancements in multi-instance generation (MIG), enabling users to define both instan…
3DIS: Depth-Driven Decoupled Instance Synthesis for Text-to-Image Generation
Dewei Zhou, Ji Xie, Zongxin Yang +1
The increasing demand for controllable outputs in text-to-image generation has spurred advancements in multi-instance generation (MIG), allowing users to define both instance layou…