Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias

CVPR, pp. 11067-11075, 2020.

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We proposed two simple yet effective methods to decorrelate feature representations of a biased category from its context

Abstract:

Existing models often leverage co-occurrences between objects and their context to improve recognition accuracy. However, strongly relying on context risks a model's generalizability, especially when typical co-occurrence patterns are absent. This work focuses on addressing such contextual biases to improve the robustness of the learnt ...More

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