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Found 6 papers, 3 papers with code
Triplet Contrastive Learning for Unsupervised Vehicle Re-identification
For the inter-class instance, a hybrid contrastive loss (HCL) re-defines the sample correlations by approaching the positive cluster features and leaving the all negative instance features.
HSGNet: Object Re-identification with Hierarchical Similarity Graph Network
Secondly, we divide the feature map along with the spatial and channel directions in each hierarchical graph.
A Competitive Method for Dog Nose-print Re-identification
Vision-based pattern identification (such as face, fingerprint, iris etc.)
GiT: Graph Interactive Transformer for Vehicle Re-identification
In the macro view, a list of GiT blocks are stacked to build a vehicle re-identification model, in where graphs are to extract discriminative local features within patches and transformers are to extract robust global features among patches.
A Competitive Method to VIPriors Object Detection Challenge
In this report, we introduce the technical details of our submission to the VIPriors object detection challenge.
Exploring Spatial Significance via Hybrid Pyramidal Graph Network for Vehicle Re-identification
Secondly, a novel pyramidal graph network (PGN) is designed to comprehensively explore the spatial significance of feature maps at multiple scales.
