11 citations · 33 across the 13 of their papers we have counts for
4 papers · 1 filter
GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration
Xiangtao Kong, Jixin Zhao, Lingchen Sun +2
Real-world image restoration (IR) is bottlenecked by the scarcity of high-quality paired training data. Synthetic datasets are abundant but often fail to model real-world degradati…
TunerDiT: Training-free Progressive Steering of Diffusion Transformer for Multi-Event Video Generation
Ruotong Liao, Guowen Huang, Qing Cheng +6
Text-to-video (T2V) generation faces challenging questions when generating videos with long horizons containing multiple events. Inspired by the intrinsics of the diffusion process…
Rethinking Structure Preservation in Text-Guided Image Editing with Visual Autoregressive Models
Tao Xia, Jiawei Liu, Yukun Zhang +3
Visual autoregressive (VAR) models have recently emerged as a promising family of generative models, enabling a wide range of downstream vision tasks such as text-guided image edit…
Restoration Adaptation for Semantic Segmentation on Low Quality Images
Kai Guan, Rongyuan Wu, Shuai Li +3
In real-world scenarios, the performance of semantic segmentation often deteriorates when processing low-quality (LQ) images, which may lack clear semantic structures and high-freq…