1 citations · 2 across the 7 of their papers we have counts for
8 papers
MAR-GRPO: Stabilized GRPO for AR-diffusion Hybrid Image Generation
Xiaoxiao Ma, Jiachen Lei, Tianfei Ren +6
Reinforcement learning (RL) has been successfully applied to autoregressive (AR) and diffusion models. However, extending RL to hybrid AR-diffusion frameworks remains challenging d…
InfoScale: Unleashing Training-free Variable-scaled Image Generation via Effective Utilization of Information
Guohui Zhang, Jiangtong Tan, Linjiang Huang +4
Diffusion models (DMs) have become dominant in visual generation but suffer performance drop when tested on resolutions that differ from the training scale, whether lower or higher…
FreeDNA: Endowing Domain Adaptation of Diffusion-Based Dense Prediction with Training-Free Domain Noise Alignment
Hang Xu, Jie Huang, Linjiang Huang +3
Domain Adaptation(DA) for dense prediction tasks is an important topic, which enhances the dense prediction model's performance when tested on its unseen domain. Recently, with the…
Adaptive Dropout: Unleashing Dropout across Layers for Generalizable Image Super-Resolution
Hang Xu, Wei Yu, Jiangtong Tan +2
Blind Super-Resolution (blind SR) aims to enhance the model's generalization ability with unknown degradation, yet it still encounters severe overfitting issues. Some previous meth…
FreePCA: Integrating Consistency Information across Long-short Frames in Training-free Long Video Generation via Principal Component Analysis
Jiangtong Tan, Hu Yu, Jie Huang +2
Long video generation involves generating extended videos using models trained on short videos, suffering from distribution shifts due to varying frame counts. It necessitates the…
AB-Cache: Training-Free Acceleration of Diffusion Models via Adams-Bashforth Cached Feature Reuse
Zichao Yu, Zhen Zou, Guojiang Shao +6
Diffusion models have demonstrated remarkable success in generative tasks, yet their iterative denoising process results in slow inference, limiting their practicality. While exist…
DiffLoss: unleashing diffusion model as constraint for training image restoration network
Jiangtong Tan, Feng Zhao
Image restoration aims to enhance low quality images, producing high quality images that exhibit natural visual characteristics and fine semantic attributes. Recently, the diffusio…
FreqMamba: Viewing Mamba from a Frequency Perspective for Image Deraining
Zou Zhen, Yu Hu, Zhao Feng
Images corrupted by rain streaks often lose vital frequency information for perception, and image deraining aims to solve this issue which relies on global and local degradation mo…