The Devil is in the Frequency: Geminated Gestalt Autoencoder for
Self-Supervised Visual Pre-Training

The Devil is in the Frequency: Geminated Gestalt Autoencoder for Self-Supervised Visual Pre-Training

18 April 2022

Xin Li

Papers citing "The Devil is in the Frequency: Geminated Gestalt Autoencoder for Self-Supervised Visual Pre-Training"

8 / 8 papers shown

Title
DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation Hao Phung Quan Dao T. Dao Hoang Phan Dimitris Metaxas Anh Tran Mamba 60 3 0 06 Nov 2024
MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis Tianhong Li Huiwen Chang Shlok Kumar Mishra Han Zhang Dina Katabi Dilip Krishnan 19 149 0 16 Nov 2022
Towards Sustainable Self-supervised Learning Shanghua Gao Pan Zhou Mingg-Ming Cheng Shuicheng Yan CLL 25 7 0 20 Oct 2022
Contrastive Masked Autoencoders are Stronger Vision Learners Zhicheng Huang Xiaojie Jin Cheng Lu Qibin Hou Mingg-Ming Cheng Dongmei Fu Xiaohui Shen Jiashi Feng 26 146 0 27 Jul 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 2021
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions Wenhai Wang Enze Xie Xiang Li Deng-Ping Fan Kaitao Song Ding Liang Tong Lu Ping Luo Ling Shao ViT 263 3,538 0 24 Feb 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 253 4,735 0 24 Feb 2021