9 papers
UHD-GPGNet: UHD Video Denoising via Gaussian-Process-Guided Local Spatio-Temporal Modeling
Weiyuan He, Chen Wu, Pengwen Dai +6
Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chromatic stability, and maintain…
UHD Low-Light Image Enhancement via Real-Time Enhancement Methods with Clifford Information Fusion
Xiaohan Wang, Chen Wu, Dawei Zhao +8
Considering efficiency, ultra-high-definition (UHD) low-light image restoration is extremely challenging. Existing methods based on Transformer architectures or high-dimensional co…
Teacher-Guided Causal Interventions for Image Denoising: Orthogonal Content-Noise Disentanglement in Vision Transformers
Kuai Jiang, Zhaoyan Ding, Guijuan Zhang +2
Conventional image denoising models often inadvertently learn spurious correlations between environmental factors and noise patterns. Moreover, due to high-frequency ambiguity, the…
SSPFormer: Self-Supervised Pretrained Transformer for MRI Images
Jingkai Li, Xiaoze Tian, Yuhang Shen +4
The pre-trained transformer demonstrates remarkable generalization ability in natural image processing. However, directly transferring it to magnetic resonance images faces two key…
Defense against Unauthorized Distillation in Image Restoration via Feature Space Perturbation
Han Hu, Zhuoran Zheng, Chen Lyu
Knowledge distillation (KD) attacks pose a significant threat to deep model intellectual property by enabling adversaries to train student networks using a teacher model's outputs.…
Foggy Crowd Counting: Combining Physical Priors and KAN-Graph
Yuhao Wang, Zhuoran Zheng, Han Hu +3
Aiming at the key challenges of crowd counting in foggy environments, such as long-range target blurring, local feature degradation, and image contrast attenuation, this paper prop…
Hazy Pedestrian Trajectory Prediction via Physical Priors and Graph-Mamba
Jian Chen, Zhuoran Zheng, Han Hu +4
To address the issues of physical information degradation and ineffective pedestrian interaction modeling in pedestrian trajectory prediction under hazy weather conditions, we prop…
FlowLUT: Efficient Image Enhancement via Differentiable LUTs and Iterative Flow Matching
Liubing Hu, Chen Wu, Anrui Wang +3
Deep learning-based image enhancement methods face a fundamental trade-off between computational efficiency and representational capacity. For example, although a conventional thre…
VAMamba: An Efficient Visual Adaptive Mamba for Image Restoration
Han Hu, Zhuoran Zheng, Liang Li +1
Recent Mamba-based image restoration methods have achieved promising results but remain limited by fixed scanning patterns and inefficient feature utilization. Conventional Mamba a…