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Found 4 papers, 2 papers with code
Recognizable Information Bottleneck
The recent PAC-Bayes IB uses information complexity instead of information compression to establish a connection with the mutual information generalization bound.
Deep Generative Mixture Model for Robust Imbalance Classification
In this paper, a deep generative classifier is proposed to mitigate this issue via both model perturbation and data perturbation.
Siamese transformer with hierarchical concept embedding for fine-grained image recognition
In particular, one subnetwork is for coarse-scale patches to learn the discriminative regions with the aid of the innate multi-head self-attention mechanism of the transformer.
Learning Target-aware Representation for Visual Tracking via Informative Interactions
The proposed GIM module and InBN mechanism are general and applicable to different backbone types including CNN and Transformer for improvements, as evidenced by our extensive experiments on multiple benchmarks.
