Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks

22 November 2021

Papers citing "Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks"

5 / 5 papers shown

Title
Local Manifold Augmentation for Multiview Semantic Consistency Yu Yang Wing Yin Cheung Chang-rui Liu Xiang Ji 31 1 0 05 Nov 2022
HyperNet: Self-Supervised Hyperspectral Spatial-Spectral Feature Understanding Network for Hyperspectral Change Detection Meiqi Hu Chen Wu L. Zhang SSL 26 57 0 20 Jul 2022
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 314 5,775 0 29 Apr 2021
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location O. Kayhan J. C. V. Gemert 209 232 0 16 Mar 2020
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 267 3,369 0 09 Mar 2020