Dec 22, 2014 · This paper presents experiments extending the work of Ba et al. (2014) on recurrent neural models for attention into less constrained visual environments.
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We propose an architecture for fine-grained visual categorization that approaches expert human performance in the classification of bird species. Our ...
This paper presents experiments extending the work of Ba et al. (2014) on recurrent neural models for attention into less constrained visual environments, ...
Nov 2, 2021 · Our result reveals that integrating human attention knowledge benefits classification effectively, eg improving the baseline by 4.38% on CXR.
Missing: Categorization. | Show results with:Categorization.
Attention mechanism has demonstrated great potential in fine-grained visual recognition tasks. In this paper, we present a counterfactual attention learning ...
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This paper proposed a Category Attention Transfer CNN (CAT-CNN) to address the efficiency issue in solving FGVC problems.
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May 3, 2024 · This study introduces a new network model for fine-grained image classification, which utilizes a hybrid attention approach.
Fine-grained visual categorization is a classification task for distinguishing categories with high intra-class and small inter-class variance.