PyTorch implementation of CNNs for CIFAR benchmark
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Updated
Feb 20, 2021 - Python
PyTorch implementation of CNNs for CIFAR benchmark
CAIRI Supervised, Semi- and Self-Supervised Visual Representation Learning Toolbox and Benchmark
face recognition training project(pytorch)
Implementation of the mixup training method
🛠 Toolbox to extend PyTorch functionalities
TextAugment: Text Augmentation Library
Oriented Object Detection: Oriented RepPoints + Swin Transformer/ReResNet
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)
Official PyTorch implementation of DiffuseMix : Label-Preserving Data Augmentation with Diffusion Models (CVPR'2024)
mixup: Beyond Empirical Risk Minimization
[CVPR 2022] CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision
Official Implementation of AlignMixup - CVPR 2022
[IEEE TMI 2024] Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification
[IJCAI 2023] Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
An implementation of MobileNetV3 with pyTorch
Official pytorch implementation of NeurIPS 2022 paper, TokenMixup
Source codes for the paper "Local Additivity Based Data Augmentation for Semi-supervised NER"
Official adversarial mixup resynthesis repository
Exploring mixup strategies for text classification
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