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Found 6 papers, 1 papers with code
Context Sensing Attention Network for Video-based Person Re-identification
In this work, we propose a novel Context Sensing Attention Network (CSA-Net), which improves both the frame feature extraction and temporal aggregation steps.
Batch Coherence-Driven Network for Part-aware Person Re-Identification
First, we introduce a batch coherence-guided channel attention (BCCA) module that highlights the relevant channels for each respective part from the output of a deep backbone model.
Multi-task Learning with Coarse Priors for Robust Part-aware Person Re-identification
MPN has three key advantages: 1) it does not need to conduct body part detection in the inference stage; 2) its model is very compact and efficient for both training and testing; 3) in the training stage, it requires only coarse priors of body part locations, which are easy to obtain.
Ranked #5 on
Person Re-Identification
on CUHK03 detected
CDPM: Convolutional Deformable Part Models for Semantically Aligned Person Re-identification
Part-level representations are essential for robust person re-identification.
Active Image Synthesis for Efficient Labeling
The great success achieved by deep neural networks attracts increasing attention from the manufacturing and healthcare communities.
Generative Invertible Networks (GIN): Pathophysiology-Interpretable Feature Mapping and Virtual Patient Generation
Machine learning methods play increasingly important roles in pre-procedural planning for complex surgeries and interventions.
