Alternatives and similar repositories for Adv-SS-Pretraining:

Users that are interested in Adv-SS-Pretraining are comparing it to the libraries listed below

• PKUAI26 / AT-CNN
  Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
  ☆65Updated 5 years ago
• garyzhao / ME-ADA
  "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).
  ☆50Updated 4 years ago
• mancinimassimiliano / pytorch_wbn
  PyTorch implementation of Weighted Batch-Normalization layers
  ☆37Updated 4 years ago
• YU1ut / JointOptimization
  Code for 'Joint Optimization Framework for Learning with Noisy Labels'
  ☆38Updated 6 years ago
• bfshi / InfoDrop
  Code for our paper "Informative Dropout for Robust Representation Learning: A Shape-bias Perspective" (ICML 2020)
  ☆125Updated 2 years ago
• tingxueronghua / pytorch-classification-advprop
  ☆107Updated 2 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 2 years ago
• VITA-Group / Once-for-All-Adversarial-Training
  [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…
  ☆43Updated 3 years ago
• cihangxie / SmoothAdversarialTraining
  Smooth Adversarial Training
  ☆67Updated 4 years ago
• LiYingwei / ShapeTextureDebiasedTraining
  Code and models for the paper Shape-Texture Debiased Neural Network Training (ICLR 2021)
  ☆108Updated last year
• hankook / SLA
  Self-supervised Label Augmentation via Input Transformations (ICML 2020)
  ☆104Updated 4 years ago
• prithv1 / DMG
  Code for our ECCV paper -- "Learning to Balance Specificity and Invariance for In and Out of Domain Generalization"
  ☆54Updated 4 years ago
• qinenergy / adanet
  [ICCV 2019 oral] Code for Semi-Supervised Learning by Augmented Distribution Alignment
  ☆62Updated 2 years ago
• minyoungg / wmigftl
  models and tools for -What makes ImageNet good for Transfer Learning?
  ☆25Updated 6 years ago
• RoyalVane / ASM
  ( NeurIPS 2020 ) Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation
  ☆70Updated 3 years ago
• philiptheother / FeatureDecoupling
  Self-Supervised Representation Learning by Rotation Feature Decoupling
  ☆95Updated 5 years ago
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 4 years ago
• meijieru / fast_advprop
  [ICLR 2022]: Fast AdvProp
  ☆34Updated 2 years ago
• pedro-morgado / nettailor
  Source code accompanying our CVPR 2019 paper: "NetTailor: Tuning the architecture, not just the weights."
  ☆52Updated 3 years ago
• cvl-umass / ssl-evaluation
  Evaluation of semi-supervised learning on challenging datasets
  ☆35Updated 3 years ago
• AhmedAyad89 / Consitent-Prototypical-Networks-Semi-Supervised-Few-Shot-Learning
  ☆19Updated 5 years ago
• HAHA-DL / Episodic-DG
  This is the repo for the paper "Episodic Training for Domain Generalization" https://arxiv.org/abs/1902.00113
  ☆57Updated last year
• hankook / AugSelf
  ☆44Updated 3 years ago
• yueatsprograms / uda_release
  Unsupervised Domain Adaptation through Self-Supervision
  ☆79Updated 3 years ago
• Simon4Yan / Meta-set
  Automatic model evaluation (AutoEval) in CVPR'21&TPAMI'22
  ☆36Updated 2 years ago
• VITA-Group / Adversarial-Contrastive-Learning
  [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang
  ☆113Updated 3 years ago
• VITA-Group / CV_LTH_Pre-training
  [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…
  ☆68Updated 2 years ago
• HaohanWang / HEX
  Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out
  ☆27Updated 3 years ago
• bhheo / BSS_distillation
  Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)
  ☆70Updated 5 years ago
• bethgelab / game-of-noise
  Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image cor…
  ☆62Updated last year