Adversarial Auto-Augment with Label Preservation: A Representation
Learning Principle Guided Approach

Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach

2 November 2022

Furong Huang

Papers citing "Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach"

9 / 9 papers shown

Title
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation Mucong Ding Bang An Yuancheng Xu Anirudh Satheesh Furong Huang 19 1 0 03 Oct 2024
Learning Tree-Structured Composition of Data Augmentation Dongyue Li Kailai Chen P. Radivojac Hongyang R. Zhang 36 1 0 26 Aug 2024
Boosting Unconstrained Face Recognition with Targeted Style Adversary Mohammad Saeed Ebrahimi Saadabadi Sahar Rahimi Malakshan Seyed Rasoul Hosseini Nasser M. Nasrabadi CVBM 26 0 0 14 Aug 2024
ARoFace: Alignment Robustness to Improve Low-Quality Face Recognition Mohammad Saeed Ebrahimi Saadabadi Sahar Rahimi Malakshan Ali Dabouei Nasser M. Nasrabadi CVBM AAML 22 3 0 20 Jul 2024
Investigating the Quality of DermaMNIST and Fitzpatrick17k Dermatological Image Datasets Kumar Abhishek Aditi Jain Ghassan Hamarneh 33 2 0 25 Jan 2024
Data Optimization in Deep Learning: A Survey Ou Wu Rujing Yao 28 1 0 25 Oct 2023
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification Jiancheng Yang Rui Shi D. Wei Zequan Liu Lin Zhao B. Ke Hanspeter Pfister Bingbing Ni VLM 161 645 0 27 Oct 2021
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling Bowen Zhang Yidong Wang Wenxin Hou Hao Wu Jindong Wang Manabu Okumura T. Shinozaki AAML 215 861 0 15 Oct 2021
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 244 1,276 0 06 Mar 2017