ImageNet-trained CNNs are not biased towards texture: Revisiting feature reliance through controlled suppression

NeurIPSOral2025

Authors
Tom Burgert, Oliver Stoll, Paolo Rota, Begüm Demir
Affiliation
Technische Universität Berlin
Venue
NeurIPS 2025
Track
Oral

TL;DR

We revisit the texture bias hypothesis in CNNs by proposing a domain-agnostic suppression protocol, finding that contrary to prior claims, CNNs primarily rely on local shape instead of texture features.

Opening excerpt from the authors’ abstract. source

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