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Found 9 papers, 0 papers with code
A Benchmark for Gait Recognition under Occlusion Collected by Multi-Kinect SDAS
We collect a new gait recognition database called OG RGB+D database, which breaks through the limitation of other gait databases and includes multimodal gait data of various occlusions (self-occlusion, active occlusion, and passive occlusion) by our multiple synchronous Azure Kinect DK sensors data acquisition system (multi-Kinect SDAS) that can be also applied in security situations.
Large-Scale Unsupervised Person Re-Identification with Contrastive Learning
In particular, most existing unsupervised and domain adaptation ReID methods utilize only the public datasets in their experiments, with labels removed.
Dynamic Image Restoration and Fusion Based on Dynamic Degradation
In addition, a dynamic degradation kernel is proposed to improve the robustness of image restoration and fusion.
AE-Netv2: Optimization of Image Fusion Efficiency and Network Architecture
Finally, we explore the commonness and characteristics of different image fusion tasks, which provides a research basis for further research on the continuous learning characteristics of human brain in the field of image fusion.
AE-Net: Autonomous Evolution Image Fusion Method Inspired by Human Cognitive Mechanism
Firstly, the relationship between human brain cognitive mechanism and image fusion task is analyzed and a physical model is established to simulate human brain cognitive mechanism.
JointsGait:A model-based Gait Recognition Method based on Gait Graph Convolutional Networks and Joints Relationship Pyramid Mapping
However, appearance features suffer from external factors which can cause drastic appearance variations, e. g. clothing.
Cross-Modal Image Fusion Theory Guided by Subjective Visual Attention
In order to improve the robustness and contextual awareness of image fusion tasks, we proposed a multi-task auxiliary learning image fusion theory guided by subjective attention.
Non-linear and Selective Fusion of Cross-Modal Images
The human visual perception system has strong robustness in image fusion.
A Cross-Modal Image Fusion Method Guided by Human Visual Characteristics
The characteristics of feature selection, nonlinear combination and multi-task auxiliary learning mechanism of the human visual perception system play an important role in real-world scenarios, but the research of image fusion theory based on the characteristics of human visual perception is less.
