Are Large-scale Datasets Necessary for Self-Supervised Pre-training?

Are Large-scale Datasets Necessary for Self-Supervised Pre-training?

20 December 2021

Alaaeldin El-Nouby

Gautier Izacard

Papers citing "Are Large-scale Datasets Necessary for Self-Supervised Pre-training?"

9 / 109 papers shown

Title
Corrupted Image Modeling for Self-Supervised Visual Pre-Training Yuxin Fang Li Dong Hangbo Bao Xinggang Wang Furu Wei 17 87 0 07 Feb 2022
Context Autoencoder for Self-Supervised Representation Learning Xiaokang Chen Mingyu Ding Xiaodi Wang Ying Xin Shentong Mo Yunhao Wang Shumin Han Ping Luo Gang Zeng Jingdong Wang SSL 45 386 0 07 Feb 2022
SLIP: Self-supervision meets Language-Image Pre-training Norman Mu Alexander Kirillov David A. Wagner Saining Xie VLM CLIP 60 476 0 23 Dec 2021
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 305 7,434 0 11 Nov 2021
VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data D. Bashkirova Dan Hendrycks Donghyun Kim Samarth Mishra Kate Saenko Kuniaki Saito Piotr Teterwak Ben Usman OOD 10 19 0 23 Jul 2021
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
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 255 4,777 0 24 Feb 2021
Pre-training without Natural Images Hirokatsu Kataoka Kazushige Okayasu Asato Matsumoto Eisuke Yamagata Ryosuke Yamada Nakamasa Inoue Akio Nakamura Y. Satoh 79 116 0 21 Jan 2021
CrossTransformers: spatially-aware few-shot transfer Carl Doersch Ankush Gupta Andrew Zisserman ViT 201 330 0 22 Jul 2020