On the Robustness of Self-Supervised Representations for Multi-view Object Classification
In this post, I’ll talk about a paper we recently published on the robustness of self-supervised representation with respective to viewpoint variation - one of the core tenants of any capable vision system. At this point, it is known that vision models pretrained using self-supervised objectives outperform standard supervised pretraining on a set of common, standard benchmark datasets such as ImageNet, CIFAR10, COCO, and Birdsnap. However, these datasets all serve to evaluate these models in a very narrow aspect - simple object classification performance.
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