Figure 1: We show intriguing properties of ViT including impressive robustness to (a) severe occlusions, (b) distributional shifts (e.g., stylization to remove texture cues), (c) adversarial perturbations, and (d) patch permutations. Furthermore, our ViT models trained to focus on shape cues ...
论文: Intriguing Properties of Vision Transformers代码: Muzammal-Naseer/Intriguing-Properties-of-Vision-Transformers导语:随着Transformer模型在NLP领域的火热,近年来这股热潮也席卷到了视觉领域。随着…
Transformer/non-local has strong global context modeling ability and has shown its great promise in various computer vision tasks. Some transformer-based image restoration methods have been proposed, such as SwinIR (Liang et al. 2021), Restormer (Zamir et al. 2022) and Uformer (Wang et al....