Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …

Multimodal emotion recognition aims to identify human emotions from text, audio, and visual
modalities. Previous methods either explore correlations between different modalities or …

This paper introduces a powerful channel augmented joint learning strategy for the visible-
infrared recognition problem. For data augmentation, most existing methods directly adopt …

Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality pedestrian
retrieval problem. Due to the large intra-class variations and cross-modality discrepancy with …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

This paper introduces a simple yet powerful channel augmentation for visible-infrared re-
identification. Most existing augmentation operations designed for single-modality visible …

Matching person images between the daytime visible modality and night-time infrared
modality (VI-ReID) is a challenging cross-modality pedestrian retrieval problem. Existing …

Improving the performance of face forgery detectors often requires more identity-swapped
images of higher-quality. One core objective of identity swap** is to generate identity …

Matching the daytime visible and nighttime infrared person images, namely visible infrared
person re-identification (VI-ReID), is a challenging cross-modality retrieval problem. Due to …

Federated human activity recognition (FHAR) has attracted much attention due to its great
potential in privacy protection. Existing FHAR methods can collaboratively learn a global …