Deep Feature Factorization For Concept Discovery
2018-06-26ECCV 2018Code Available0· sign in to hype
Edo Collins, Radhakrishna Achanta, Sabine Süsstrunk
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- github.com/jacobgil/pytorch-grad-campytorch★ 12,704
- github.com/edocollins/DFFpytorch★ 0
- github.com/MindSpore-scientific/code-12/tree/main/Deep_Feature_Factorization_For_Concept_Discoverymindspore★ 0
- github.com/MindSpore-scientific-2/code-9/tree/main/Deep_Feature_Factorization_For_Concept_Discoverymindspore★ 0
Abstract
We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images. We use DFF to gain insight into a deep convolutional neural network's learned features, where we detect hierarchical cluster structures in feature space. This is visualized as heat maps, which highlight semantically matching regions across a set of images, revealing what the network `perceives' as similar. DFF can also be used to perform co-segmentation and co-localization, and we report state-of-the-art results on these tasks.