5 papers
Multi-Modal Object Re-Identification with Dual Semantic Guidance and Global-Local Mutual Modulation
Weixiang Zhou, Xingguo Xu, Yuhao Wang +4
Multi-modal object Re-Identification (ReID) aims to retrieve target instances by leveraging complementary information across modalities. However, existing methods suffer from two c…
Scene Prior Filtering for Depth Super-Resolution
Zhengxue Wang, Zhiqiang Yan, Ming-Hsuan Yang +4
Multi-modal fusion serves as a cornerstone for successful depth map super-resolution. However, commonly used fusion strategies, such as addition and concatenation, fall short of ef…
Learning Deblurring Texture Prior from Unpaired Data with Diffusion Model
Chengxu Liu, Lu Qi, Jinshan Pan +2
Since acquiring large amounts of realistic blurry-sharp image pairs is difficult and expensive, learning blind image deblurring from unpaired data is a more practical and promising…
Frequency Domain-Based Diffusion Model for Unpaired Image Dehazing
Chengxu Liu, Lu Qi, Jinshan Pan +2
Unpaired image dehazing has attracted increasing attention due to its flexible data requirements during model training. Dominant methods based on contrastive learning not only intr…
Efficient Visual State Space Model for Image Deblurring
Lingshun Kong, Jiangxin Dong, Jinhui Tang +2
Convolutional neural networks (CNNs) and Vision Transformers (ViTs) have achieved excellent performance in image restoration. While ViTs generally outperform CNNs by effectively ca…