Efficient Image Pre-Training with Siamese Cropped Masked Autoencoders

arXiv:2403.17823v1 Announce Type: new
Abstract: Self-supervised pre-training of image encoders is omnipresent in the literature, particularly following the introduction of Masked autoencoders (MAE). Current efforts attempt to learn object-centric representations from motion in videos. In particular, SiamMAE recently introduced a Siamese network, training a shared-weight encoder from two frames of a video with a high asymmetric masking ratio (95%). In this work, we propose CropMAE, an alternative approach to the Siamese pre-training introduced by SiamMAE. Our method specifically differs by …

arxiv autoencoders cs.cv image pre-training training type