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cs.CV2026
CLEAR: Unlocking Generative Potential for Degraded Image Understanding in Unified Multimodal Models
Xiangzhao Hao, Zefeng Zhang, Zhenyu Zhang +6
Image degradation from blur, noise, compression, and poor illumination severely undermines multimodal understanding in real-world settings. Unified multimodal models that combine u…
cs.CV2024
Local Conditional Controlling for Text-to-Image Diffusion Models
Yibo Zhao, Liang Peng, Yang Yang +9
Diffusion models have exhibited impressive prowess in the text-to-image task. Recent methods add image-level structure controls, e.g., edge and depth maps, to manipulate the genera…
cs.CV2024
LoRA-Composer: Leveraging Low-Rank Adaptation for Multi-Concept Customization in Training-Free Diffusion Models
Yang Yang, Wen Wang, Liang Peng +8
Customization generation techniques have significantly advanced the synthesis of specific concepts across varied contexts. Multi-concept customization emerges as the challenging ta…