Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.

Overview

Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021)

Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu

This is the official Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.

This implementation is based on these repositories:

Main Requirements

  • torch == 1.0.1
  • torchvision == 0.2.0
  • Python 3

Training Examples

  • Mixed Single Thumbnail
python train.py -d [datasetlocation] --depth 50 --mode mst --size 112 --lam 0.25 --participation_rate 0.8
  • Self Thumbnail
python train.py -d [datasetlocation] --depth 50 --mode st --size 112 --lam 0.25 --participation_rate 0.8

Results

  • ImageNet Results
Model Accuracy (%)
ResNet50 + CutMix 78.60*
ResNet50 + Cut-Thumbnail (ST) 77.74
ResNet50 + Cut-Thumbnail (MST) 79.21

* denotes results reported in the original papers.

  • CIFAR-100 Results
Model Accuracy (%)
WideResNet-28-10 + Cut-Thumbnail (ST) 81.41
WideResNet-28-10 + Cut-Thumbnail (MST) 83.35
  • CUB-200-2011 Results
Model Accuracy (%)
ResNet50 + Cut-Thumbnail (ST) 85.72
ResNet50 + Cut-Thumbnail (MST) 86.56
ResNet50 + Cut-Thumbnail (MDT) 86.72

Citation

If you find our paper and this repo useful, please cite as

@inproceedings{xie20cut-thumbnail,
    author = {Xie, Tianshu and Cheng, Xuan and Wang, Xiaomin and Liu, Minghui and Deng, Jiali and Zhou, Tao and Liu, Ming},
    title = {Cut-Thumbnail: A Novel Data Augmentation for Convolutional Neural Network},
    year = {2021},
    isbn = {9781450386517},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3474085.3475302},
    doi = {10.1145/3474085.3475302},
    booktitle = {Proceedings of the 29th ACM International Conference on Multimedia},
    pages = {1627–1635},
    numpages = {9},
    location = {Virtual Event, China},
    series = {MM '21}
}
This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim

Rakshitha Godahewa 80 Dec 30, 2022
Find-Lane-Line - Use openCV library and Python to detect the road-lane-line

Find-Lane-Line This project is to use openCV library and Python to detect the road-lane-line. Data Pipeline Step one : Color Selection Step two : Cann

Kenny Cheng 3 Aug 17, 2022
Official implementation of the paper Visual Parser: Representing Part-whole Hierarchies with Transformers

Visual Parser (ViP) This is the official implementation of the paper Visual Parser: Representing Part-whole Hierarchies with Transformers. Key Feature

Shuyang Sun 117 Dec 11, 2022
yolox_backbone is a deep-learning library and is a collection of YOLOX Backbone models.

YOLOX-Backbone yolox-backbone is a deep-learning library and is a collection of YOLOX backbone models. Install pip install yolox-backbone Load a Pret

Yonghye Kwon 21 Dec 28, 2022
Official PyTorch implementation of "BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation" (NeurIPS 2021)

BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation Official PyTorch implementation of the NeurIPS 2021 paper Mingcong Liu, Qiang

onion 462 Dec 29, 2022
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training

30 Nov 14, 2022
YoHa - A practical hand tracking engine.

YoHa - A practical hand tracking engine.

2k Jan 06, 2023
Code for Mining the Benefits of Two-stage and One-stage HOI Detection

Status: Archive (code is provided as-is, no updates expected) PPO-EWMA [Paper] This is code for training agents using PPO-EWMA and PPG-EWMA, introduce

OpenAI 33 Dec 15, 2022
Deep Reinforcement Learning for Multiplayer Online Battle Arena

MOBA_RL Deep Reinforcement Learning for Multiplayer Online Battle Arena Prerequisite Python 3 gym-derk Tensorflow 2.4.1 Dotaservice of TimZaman Seed R

Dohyeong Kim 32 Dec 18, 2022
Sequence modeling benchmarks and temporal convolutional networks

Sequence Modeling Benchmarks and Temporal Convolutional Networks (TCN) This repository contains the experiments done in the work An Empirical Evaluati

CMU Locus Lab 3.5k Jan 01, 2023
This is a repository for a No-Code object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operating systems.

OpenVINO Inference API This is a repository for an object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operati

BMW TechOffice MUNICH 68 Nov 24, 2022
Implementation of our paper 'RESA: Recurrent Feature-Shift Aggregator for Lane Detection' in AAAI2021.

RESA PyTorch implementation of the paper "RESA: Recurrent Feature-Shift Aggregator for Lane Detection". Our paper has been accepted by AAAI2021. Intro

137 Jan 02, 2023
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Zhao Jian 3.1k Jan 04, 2023
Brain tumor detection using CNN (InceptionResNetV2 Model)

Brain-Tumor-Detection Building a detection model using a convolutional neural network in Tensorflow & Keras. Used brain MRI images. InceptionResNetV2

1 Feb 13, 2022
This repo is a C++ version of yolov5_deepsort_tensorrt. Packing all C++ programs into .so files, using Python script to call C++ programs further.

yolov5_deepsort_tensorrt_cpp Introduction This repo is a C++ version of yolov5_deepsort_tensorrt. And packing all C++ programs into .so files, using P

41 Dec 27, 2022
A Fast Knowledge Distillation Framework for Visual Recognition

FKD: A Fast Knowledge Distillation Framework for Visual Recognition Official PyTorch implementation of paper A Fast Knowledge Distillation Framework f

Zhiqiang Shen 129 Dec 24, 2022
Detectron2 is FAIR's next-generation platform for object detection and segmentation.

Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up r

Facebook Research 23.3k Jan 08, 2023
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.

Pyserini Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. Retrieval using sparse re

Castorini 706 Dec 29, 2022
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels

Simple and Robust Loss Design for Multi-Label Learning with Missing Labels Official PyTorch Implementation of the paper Simple and Robust Loss Design

Xinyu Huang 28 Oct 27, 2022
Code of the paper "Shaping Visual Representations with Attributes for Few-Shot Learning (ASL)".

Shaping Visual Representations with Attributes for Few-Shot Learning This code implements the Shaping Visual Representations with Attributes for Few-S

chx_nju 9 Sep 01, 2022