RandAugment: Practical automated data augmentation with a reduced search space

30 September 2019

Papers citing "RandAugment: Practical automated data augmentation with a reduced search space"

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Title
Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces Bert Moons Parham Noorzad Andrii Skliar G. Mariani Dushyant Mehta Chris Lott Tijmen Blankevoort 137 43 0 16 Dec 2020
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi Yin Cui A. Srinivas Rui Qian Tsung-Yi Lin E. D. Cubuk Quoc V. Le Barret Zoph ISeg 226 968 0 13 Dec 2020
Imitating Interactive Intelligence Josh Abramson Arun Ahuja Iain Barr Arthur Brussee Federico Carnevale ... Greg Wayne Duncan Williams Nathaniel Wong Chen Yan Rui Zhu LM&Ro 8 71 0 10 Dec 2020
Large-Scale Generative Data-Free Distillation Liangchen Luo Mark Sandler Zi Lin A. Zhmoginov Andrew G. Howard 14 43 0 10 Dec 2020
Poisoning Semi-supervised Federated Learning via Unlabeled Data: Attacks and Defenses Yi Liu Xingliang Yuan Ruihui Zhao Cong Wang Dusit Niyato Yefeng Zheng 17 5 0 08 Dec 2020
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection He-Nan Wang Yezhen Cong Or Litany Yue Gao Leonidas J. Guibas 3DPC 31 121 0 08 Dec 2020
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization Kien Do T. Tran Svetha Venkatesh BDL 6 3 0 03 Dec 2020
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs Nikhil Kapoor C. Yuan Jonas Löhdefink Roland S. Zimmermann Serin Varghese Fabian Hüger Nico M. Schmidt Peter Schlicht Tim Fingscheidt AAML 22 4 0 02 Dec 2020
A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation Rihuan Ke Angelica Aviles-Rivero Saurabh Pandey Saikumar Reddy Carola-Bibiane Schönlieb 23 52 0 01 Dec 2020
Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering B. Lerner Guy Shiran D. Weinshall SSL 12 5 0 01 Dec 2020
MUSCLE: Strengthening Semi-Supervised Learning Via Concurrent Unsupervised Learning Using Mutual Information Maximization Hanchen Xie Mohamed E. Hussein Aram Galstyan Wael Abd-Almageed SSL 15 8 0 30 Nov 2020
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot Tasks Han-Jia Ye Lu Han De-Chuan Zhan OffRL SSL VLM 19 27 0 30 Nov 2020
Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training Shuai Zhao Liguang Zhou Wenxiao Wang D. Cai Tin Lun Lam Yangsheng Xu 17 31 0 30 Nov 2020
Leveraging Regular Fundus Images for Training UWF Fundus Diagnosis Models via Adversarial Learning and Pseudo-Labeling Lie Ju Xin Wang Xin Zhao Paul Bonnington Tom Drummond Zongyuan Ge GAN MedIm 8 40 0 27 Nov 2020
Reflective-Net: Learning from Explanations Johannes Schneider Michalis Vlachos FAtt OffRL LRM 52 18 0 27 Nov 2020
Grafit: Learning fine-grained image representations with coarse labels Hugo Touvron Alexandre Sablayrolles Matthijs Douze Matthieu Cord Hervé Jégou SSL 22 68 0 25 Nov 2020
Multiclass non-Adversarial Image Synthesis, with Application to Classification from Very Small Sample Itamar Winter D. Weinshall GAN 19 0 0 25 Nov 2020
An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation Rongchang Xie Chunyu Wang Wenjun Zeng Yizhou Wang SSL 3DH 11 26 0 25 Nov 2020
Assessing Post-Disaster Damage from Satellite Imagery using Semi-Supervised Learning Techniques Jihyeon Janel Lee Joseph Z. Xu Kihyuk Sohn W. Lu David Berthelot ... Pranav Khaitan Ke-Wei Ke Huang Kyriacos M. Koupparis Bernhard Kowatsch 15 23 0 24 Nov 2020
CoMatch: Semi-supervised Learning with Contrastive Graph Regularization Junnan Li Caiming Xiong S. Hoi SSL 19 252 0 23 Nov 2020
An Effective Anti-Aliasing Approach for Residual Networks C. N. Vasconcelos Hugo Larochelle Vincent Dumoulin Nicolas Le Roux Ross Goroshin SupR 20 32 0 20 Nov 2020
Hybrid Consistency Training with Prototype Adaptation for Few-Shot Learning Meng Ye Xiaoyu Lin Giedrius Burachas Ajay Divakaran Yi Yao 12 2 0 19 Nov 2020
An Efficient and Scalable Deep Learning Approach for Road Damage Detection Sadra Naddaf-sh M.-Mahdi Naddaf-Sh Amir R. Kashani H. Zargarzadeh 14 57 0 18 Nov 2020
FROST: Faster and more Robust One-shot Semi-supervised Training Helena E. Liu L. Smith BDL OffRL 29 1 0 18 Nov 2020
Neural Semi-supervised Learning for Text Classification Under Large-Scale Pretraining Zijun Sun Chun Fan Xiaofei Sun Yuxian Meng Fei Wu Jiwei Li 17 9 0 17 Nov 2020
Can Semantic Labels Assist Self-Supervised Visual Representation Learning? Longhui Wei Lingxi Xie Jianzhong He Jianlong Chang Xiaopeng Zhang Wen-gang Zhou Houqiang Li Qi Tian SSL 6 25 0 17 Nov 2020
Probing Predictions on OOD Images via Nearest Categories Yao-Yuan Yang Cyrus Rashtchian Ruslan Salakhutdinov Kamalika Chaudhuri AAML 12 0 0 17 Nov 2020
A comparative study of semi- and self-supervised semantic segmentation of biomedical microscopy data Nastassya Horlava A. Mironenko Sebastian Niehaus Sebastian Wagner Ingo Roeder N. Scherf SSL 10 3 0 11 Nov 2020
EfficientPose: An efficient, accurate and scalable end-to-end 6D multi object pose estimation approach Yannick Bukschat Marcus Vetter 6 110 0 09 Nov 2020
Detecting Outliers with Foreign Patch Interpolation Jeremy Tan Benjamin Hou James Batten Huaqi Qiu Bernhard Kainz MedIm 9 48 0 09 Nov 2020
Data Augmentation via Structured Adversarial Perturbations Calvin Luo H. Mobahi Samy Bengio AAML 6 5 0 05 Nov 2020
Supervised Contrastive Learning for Pre-trained Language Model Fine-tuning Beliz Gunel Jingfei Du Alexis Conneau Ves Stoyanov 10 497 0 03 Nov 2020
SapAugment: Learning A Sample Adaptive Policy for Data Augmentation Ting-Yao Hu A. Shrivastava Jen-Hao Rick Chang H. Koppula Stefan Braun Kyuyeon Hwang Ozlem Kalinli Oncel Tuzel 9 16 0 02 Nov 2020
Self-paced Data Augmentation for Training Neural Networks Tomoumi Takase Ryo Karakida H. Asoh 7 17 0 29 Oct 2020
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets Kai Han Yunhe Wang Qiulin Zhang Wei Zhang Chunjing Xu Tong Zhang 11 87 0 28 Oct 2020
An empirical study of domain-agnostic semi-supervised learning via energy-based models: joint-training and pre-training Yunfu Song Huahuan Zheng Zhijian Ou 12 0 0 25 Oct 2020
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels Valentyn Melnychuk Evgeniy Faerman I. Manakov Thomas Seidl 7 0 0 23 Oct 2020
How Data Augmentation affects Optimization for Linear Regression Boris Hanin Yi Sun 10 16 0 21 Oct 2020
Combining Ensembles and Data Augmentation can Harm your Calibration Yeming Wen Ghassen Jerfel Rafael Muller Michael W. Dusenberry Jasper Snoek Balaji Lakshminarayanan Dustin Tran UQCV 24 63 0 19 Oct 2020
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding Yanru Qu Dinghan Shen Yelong Shen Sandra Sajeev Jiawei Han Weizhu Chen 130 66 0 16 Oct 2020
Does Data Augmentation Benefit from Split BatchNorms Amil Merchant Barret Zoph E. D. Cubuk 13 9 0 15 Oct 2020
HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network P. Yuan Shufei Lin Cheng Cui Yuning Du Ruoyu Guo Dongliang He Errui Ding Shumin Han 14 43 0 15 Oct 2020
Self-Supervised Domain Adaptation with Consistency Training Liang Xiao J. Xu D. Zhao Z. Wang L. Wang Y. Nie B. Dai 15 14 0 15 Oct 2020
Viewmaker Networks: Learning Views for Unsupervised Representation Learning Alex Tamkin Mike Wu Noah D. Goodman SSL 17 64 0 14 Oct 2020
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy Sharib Ali Mariia Dmitrieva N. Ghatwary Sophia Bano Gorkem Polat ... Terry Tran-Nguyen A. Bailey B. Braden J. East J. Rittscher 11 10 0 12 Oct 2020
Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning Tao Han Junyu Gao Yuan. Yuan Qi. Wang 11 26 0 12 Oct 2020
Population Based Training for Data Augmentation and Regularization in Speech Recognition Daniel Haziza Jérémy Rapin Gabriel Synnaeve 18 1 0 08 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 323 0 07 Oct 2020
Exploring the Interchangeability of CNN Embedding Spaces David G. McNeely-White Benjamin Sattelberg Nathaniel Blanchard Ross Beveridge CVBM 9 1 0 05 Oct 2020
WeMix: How to Better Utilize Data Augmentation Yi Tian Xu Asaf Noy Ming Lin Qi Qian Hao Li R. L. Jin 21 16 0 03 Oct 2020