728 citations · 1k across the 20 of their papers we have counts for
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CIM: Class-Irrelevant Mapping for Few-Shot Classification
Shuai Shao, Lei Xing, Yixin Chen +3
Few-shot classification (FSC) is one of the most concerned hot issues in recent years. The general setting consists of two phases: (1) Pre-train a feature extraction model (FEM) wi…
Secure Reversible Data Hiding in Encrypted Images Using Cipher-Feedback Secret Sharing
Zhongyun Hua, Yanxiang Wang, Shuang Yi +2
Reversible data hiding in encrypted images (RDH-EI) has attracted increasing attention, since it can protect the privacy of original images while the embedded data can be exactly e…
Detection of Deepfake Videos Using Long Distance Attention
Wei Lu, Lingyi Liu, Junwei Luo +3
With the rapid progress of deepfake techniques in recent years, facial video forgery can generate highly deceptive video contents and bring severe security threats. And detection o…
LineCounter: Learning Handwritten Text Line Segmentation by Counting
Deng Li, Yue Wu, Yicong Zhou
Handwritten Text Line Segmentation (HTLS) is a low-level but important task for many higher-level document processing tasks like handwritten text recognition. It is often formulate…
SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization
Deng Li, Yue Wu, Yicong Zhou
Inspired by the classic Sauvola local image thresholding approach, we systematically study it from the deep neural network (DNN) perspective and propose a new solution called Sauvo…
Bridging the Distribution Gap of Visible-Infrared Person Re-identification with Modality Batch Normalization
Wenkang Li, Qi Ke, Wenbin Chen +1
Visible-infrared cross-modality person re-identification (VI-ReID), whose aim is to match person images between visible and infrared modality, is a challenging cross-modality image…
Unified Batch All Triplet Loss for Visible-Infrared Person Re-identification
Wenkang Li, Ke Qi, Wenbin Chen +1
Visible-Infrared cross-modality person re-identification (VI-ReID), whose aim is to match person images between visible and infrared modality, is a challenging cross-modality image…