72 citations · 124 across the 7 of their papers we have counts for
7 papers
Learning Modal-Invariant and Temporal-Memory for Video-based Visible-Infrared Person Re-Identification
Xinyu Lin, Jinxing Li, Zeyu Ma +5
Thanks for the cross-modal retrieval techniques, visible-infrared (RGB-IR) person re-identification (Re-ID) is achieved by projecting them into a common space, allowing person Re-I…
Global-Local Stepwise Generative Network for Ultra High-Resolution Image Restoration
Xin Feng, Haobo Ji, Wenjie Pei +2
While the research on image background restoration from regular size of degraded images has achieved remarkable progress, restoring ultra high-resolution (e.g., 4K) images remains…
HIPA: Hierarchical Patch Transformer for Single Image Super Resolution
Qing Cai, Yiming Qian, Jinxing Li +4
Transformer-based architectures start to emerge in single image super resolution (SISR) and have achieved promising performance. Most existing Vision Transformers divide images int…
Pseudocylindrical Convolutions for Learned Omnidirectional Image Compression
Mu Li, Kede Ma, Jinxing Li +1
Although equirectangular projection (ERP) is a convenient form to store omnidirectional images (also known as 360-degree images), it is neither equal-area nor conformal, thus not f…
Pedestrian Detection by Exemplar-Guided Contrastive Learning
Zebin Lin, Wenjie Pei, Fanglin Chen +2
Typical methods for pedestrian detection focus on either tackling mutual occlusions between crowded pedestrians, or dealing with the various scales of pedestrians. Detecting pedest…
Deep-Masking Generative Network: A Unified Framework for Background Restoration from Superimposed Images
Xin Feng, Wenjie Pei, Zihui Jia +3
Restoring the clean background from the superimposed images containing a noisy layer is the common crux of a classical category of tasks on image restoration such as image reflecti…
Optimal Projection Guided Transfer Hashing for Image Retrieval
Ji Liu, Lei Zhang
Recently, learning to hash has been widely studied for image retrieval thanks to the computation and storage efficiency of binary codes. For most existing learning to hash methods,…