HTC implementation using PyTorch (supports MOSAIC/MixUp and RandomAugment)

A repository to host recent papers on Manifold Mixup.

Python package for data augmentation inspired by Mixup: Beyond Empirical Risk Minimization

CascadeRCNN implementation using PyTorch

Tensorflow2/KerasのImageDataGenerator向けのmixupの実装。

Bronze medal solution for the "Bengali.AI Handwritten Grapheme Classification" Kaggle competition

Code for the ACL 2023 long paper "Composition-contrastive Learning for Sentence Embeddings"

DualDet implementation using PyTorch

This repo implements a ViT based model with Mixup Data Augmentation method. All the models including ViT are implemented from scratch using tensorflow

An R package inspired by 'mixup: Beyond Empirical Risk Minimization'

Official implementation for ACL2021 Oral Paper: "OoMMix: Out-of-manifold Regularization in Contextual Embedding Space for Text Classification"

To evaluate the performance of each regularization method (cutout, mixup, and self-supervised rotation predictor), we apply it to the CIFAR-10 dataset using a deep residual network with a depth of 20 (ResNet20)

6-th task solution of DCASE2020

用一篇文章混淆一篇文章(比如公众号)

Python codes to implement DeMix, a DETR assisted CutMix method for image data augmentation

About Official PyTorch(MMCV) implementation of “SUMix: Mixup with Semantic and Uncertain Information” (ECCV 2024)

HTCLite implementation using PyTorch (supports MOSAIC/MixUp and RandomAugment)

Classification using Vision Transformers (ViT) and MixUp Augmentation