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Spot-the-difference self-supervised pre-training for anomaly detection and segmentation
Visual anomaly detection is commonly used in industrial quality inspection. In this paper, we
present a new dataset as well as a new self-supervised learning method for ImageNet pre …
present a new dataset as well as a new self-supervised learning method for ImageNet pre …
Contrastive and non-contrastive self-supervised learning recover global and local spectral embedding methods
Abstract Self-Supervised Learning (SSL) surmises that inputs and pairwise positive
relationships are enough to learn meaningful representations. Although SSL has recently …
relationships are enough to learn meaningful representations. Although SSL has recently …
Partial success in closing the gap between human and machine vision
A few years ago, the first CNN surpassed human performance on ImageNet. However, it
soon became clear that machines lack robustness on more challenging test cases, a major …
soon became clear that machines lack robustness on more challenging test cases, a major …
Getting aligned on representational alignment
I Sucholutsky, L Muttenthaler, A Weller, A Peng… - ar** high-level visual representation in brains and machines?
The rapid development and open-source release of highly performant computer vision
models offers new potential for examining how different inductive biases impact …
models offers new potential for examining how different inductive biases impact …
Improving neural network representations using human similarity judgments
Deep neural networks have reached human-level performance on many computer vision
tasks. However, the objectives used to train these networks enforce only that similar images …
tasks. However, the objectives used to train these networks enforce only that similar images …