Papers with Code 아카이브

2D Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/2023-MindSpore-4/Code2/tree/main/3D_DenseNet

Multi-scale Multi-band DenseNets for Audio Source Separation

https://github.com/2023-MindSpore-4/Code2/tree/main/darknet53

RealNet: Combining Optimized Object Detection with Information Fusion Depth Estimation Co-Design Method on IoT

https://github.com/2023-MindSpore-4/Code3/tree/main/Deepsort

StrongSORT: Make DeepSORT Great Again

https://github.com/2023-MindSpore-4/Code3/tree/main/E-NET

https://github.com/2023-MindSpore-4/Code3/tree/main/EfficientDet_d0

EfficientDet: Scalable and Efficient Object Detection

https://github.com/2023-MindSpore-4/Code3/tree/main/detr

DN-DETR: Accelerate DETR Training by Introducing Query DeNoising

https://github.com/2023-MindSpore-4/Code3/tree/main/efficientnet-b0

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

https://github.com/2023-MindSpore-4/Code4/tree/main/GLNet-TCYB2022-MindSpore

Global-and-Local Collaborative Learning for Co-Salient Object Detection

https://github.com/2023-MindSpore-4/Code4/tree/main/tnet_mindspore

Does Thermal Really Always Matter for RGB-T Salient Object Detection?

https://github.com/2023-MindSpore-4/Code4/tree/main/wslnet

A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid Labels

https://github.com/2023-MindSpore-4/Code6/tree/main/PVAnet

PVANet: Lightweight Deep Neural Networks for Real-time Object Detection

https://github.com/2023-MindSpore-4/Code6/tree/main/RefineDet

FSSD: Feature Fusion Single Shot Multibox Detector

https://github.com/2023-MindSpore-4/Code6/tree/main/ResNeSt50

ResNeSt: Split-Attention Networks

https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_mobilenetV2

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_mobilenetV2_FPNlite

MobileNetV2: Inverted Residuals and Linear Bottlenecks

https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet34

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet_34

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code8/tree/main/3D_DenseNet

DenseNet: Implementing Efficient ConvNet Descriptor Pyramids

https://github.com/2023-MindSpore-4/Code8/tree/main/ArbitraryStyleTransfer

Exploring the structure of a real-time, arbitrary neural artistic stylization network

https://github.com/2023-MindSpore-4/Code8/tree/main/CBAM

CBAM: Convolutional Block Attention Module

https://github.com/2023-MindSpore-4/Code8/tree/main/augvit

How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

https://github.com/2023-MindSpore-4/Code8/tree/main/centerface

CenterNet: Keypoint Triplets for Object Detection

https://github.com/2023-MindSpore-4/Code8/tree/main/centernet_det

CenterNet: Keypoint Triplets for Object Detection

https://github.com/2023-MindSpore-4/Code8/tree/main/centernet_resnet101

CenterNet: Keypoint Triplets for Object Detection

https://github.com/2023-MindSpore-4/Code8/tree/main/convnext

A ConvNet for the 2020s

https://github.com/2023-MindSpore-4/Code8/tree/main/crnn_seq2seq_ocr

The Sequence-to-Sequence Baseline for the Voice Conversion Challenge 2020: Cascading ASR and TTS

https://github.com/2023-MindSpore-4/Code9/tree/main/MaskRCNN

Mask R-CNN

https://github.com/2023-MindSpore-4/Code9/tree/main/MobileNet

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

https://github.com/2023-MindSpore-4/Code9/tree/main/OpenPose

OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/2023-MindSpore-4/Code9/tree/main/PointNet2

Frustum PointNets for 3D Object Detection from RGB-D Data

https://github.com/2023-MindSpore-4/Code9/tree/main/ResNet

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code9/tree/main/RetinaNet

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

https://github.com/2023-MindSpore-4/Code9/tree/main/ShuffleNet

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

https://github.com/2023-MindSpore-4/Code9/tree/main/SwinTransformer

Self-Supervised Learning with Swin Transformers

https://github.com/2023-MindSpore-4/Code9/tree/main/YOLOv3

YOLOv3: An Incremental Improvement

https://github.com/2024-MindSpore-1/Code10/tree/main/DRAN

DRAN: Detailed Region-Adaptive Normalization for Conditional Image Synthesis

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.