16 papers
Rarity-Aware Discrete Diffusion with Spatially Consistent Decoding for Photo-Realistic Image Super-Resolution
Ao Li, Yapeng Du, Yi Xin +5
Continuous diffusion models have become the dominant paradigm for photo-realistic image Super-Resolution (SR), but they typically formulate reconstruction as continuous signal-leve…
From Open Loop to Closed Loop: A Test-Time Iterative Optimization Framework for Reference-Consistent Image Generation
Baixuan Zhao, Xinyu Zhang, Huayu Zheng +4
While controllable image generation has made significant strides by incorporating visual reference conditions, existing methods predominantly operate as open-loop systems. They inj…
Efficient One-Step Diffusion Restoration Model with Compact Token Compression and Linear Attention
Bingtian Qiao, Yue Shi, Yingjie Zhou +3
Real-world image super-resolution aims to recover high-quality images from complex and unknown real-world degradations. However, existing generative Real-ISR methods largely inheri…
Sketch Then Paint: Hierarchical Reinforcement Learning for Diffusion Multi-Modal Large Language Models
Siqi Luo, Jianghan Shen, Yi Xin +9
Diffusion Multi-Modal Large Language Models (dMLLMs) are powerful for image generation, but optimizing them through reinforcement learning (RL) remains a major challenge. One prima…
A2BFR: Attribute-Aware Blind Face Restoration
Chenxin Zhu, Yushun Fang, Lu Liu +5
Blind face restoration (BFR) aims to recover high-quality facial images from degraded inputs, yet its inherently ill-posed nature leads to ambiguous and uncontrollable solutions. R…
A-Edit: Precise Reference-Guided Image Editing of Arbitrary Objects and Ambiguous Masks
Huayu Zheng, Guangzhao Li, Baixuan Zhao +4
We propose A^2-Edit, a unified inpainting framework for arbitrary object categories, which allows users to replace any target region with a reference object using only a coarse mas…