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Found 6 papers, 2 papers with code
Multiple Domain Experts Collaborative Learning: Multi-Source Domain Generalization For Person Re-Identification
In UDCL, a universal expert supervises the learning of domain experts and continuously gathers knowledge from all domain experts.
Layerwise Optimization by Gradient Decomposition for Continual Learning
The gradient for update should be close to the gradient of the new task, consistent with the gradients shared by all old tasks, and orthogonal to the space spanned by the gradients specific to the old tasks.
Neighbourhood-guided Feature Reconstruction for Occluded Person Re-Identification
Person images captured by surveillance cameras are often occluded by various obstacles, which lead to defective feature representation and harm person re-identification (Re-ID) performance.
Complementary Relation Contrastive Distillation
Specifically, we estimate the mutual relation in an anchor-based way and distill the anchor-student relation under the supervision of its corresponding anchor-teacher relation.
Ranked #26 on
Knowledge Distillation
on ImageNet
Improved Mutual Mean-Teaching for Unsupervised Domain Adaptive Re-ID
SDA, a domain-translation-based framework, focuses on carefully translating the source-domain images to the target domain.
COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification
To address the clothes changing person re-id problem, we construct a novel large-scale re-id benchmark named ClOthes ChAnging Person Set (COCAS), which provides multiple images of the same identity with different clothes.
