Randomized Quantization: A Generic Augmentation for Data Agnostic Self-supervised Learning

19 December 2022

Papers citing "Randomized Quantization: A Generic Augmentation for Data Agnostic Self-supervised Learning"

8 / 8 papers shown

Title
SimMAT: Exploring Transferability from Vision Foundation Models to Any Image Modality Chenyang Lei Liyi Chen Jun Cen Xiao Chen Zhen Lei Felix Heide Ziwei Liu Qifeng Chen Zhaoxiang Zhang 34 0 0 12 Sep 2024
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains Kyungeun Lee Ye Seul Sim Hye-Seung Cho Moonjung Eo Suhee Yoon Sanghyu Yoon Woohyung Lim SSL 27 5 0 13 May 2024
Revealing the Two Sides of Data Augmentation: An Asymmetric Distillation-based Win-Win Solution for Open-Set Recognition Yunbing Jia Xiaoyu Kong Fan Tang Yixing Gao Weiming Dong Yi Yang 54 2 0 28 Apr 2024
Data-Efficient Multimodal Fusion on a Single GPU Noël Vouitsis Zhaoyan Liu S. Gorti Valentin Villecroze Jesse C. Cresswell Guangwei Yu G. Loaiza-Ganem M. Volkovs 35 3 0 15 Dec 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,412 0 11 Nov 2021
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations Debidatta Dwibedi Y. Aytar Jonathan Tompson P. Sermanet Andrew Zisserman SSL 183 450 0 29 Apr 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 295 5,761 0 29 Apr 2021
Unsupervised Multi-Task Feature Learning on Point Clouds Kaveh Hassani Mike Haley SSL 3DPC 109 193 0 18 Oct 2019