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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

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보존된 평가 기록

1

코드

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

https://github.com/2023-MindSpore-1/ms-code-48

Point Transformer

https://github.com/2023-MindSpore-1/ms-code-51

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/2023-MindSpore-1/ms-code-59

YOLOv3: An Incremental Improvement

https://github.com/2023-MindSpore-1/ms-code-6/tree/main/CBAM

CBAM: Convolutional Block Attention Module

https://github.com/2023-MindSpore-1/ms-code-6/tree/main/CascadeRCNN

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

https://github.com/2023-MindSpore-1/ms-code-6/tree/main/centernet

CenterNet: Keypoint Triplets for Object Detection

https://github.com/2023-MindSpore-1/ms-code-6/tree/main/centernet_det

CenterNet: Keypoint Triplets for Object Detection

https://github.com/2023-MindSpore-1/ms-code-6/tree/main/cnn_direction_model

Structured Sparse R-CNN for Direct Scene Graph Generation

https://github.com/2023-MindSpore-1/ms-code-60

YOLOv3: An Incremental Improvement

https://github.com/2023-MindSpore-1/ms-code-66

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/2023-MindSpore-1/ms-code-67

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/2023-MindSpore-1/ms-code-69

End-to-End Object Detection with Transformers

https://github.com/2023-MindSpore-1/ms-code-7/tree/main/TokenFusion

Multimodal Token Fusion for Vision Transformers

https://github.com/2023-MindSpore-1/ms-code-7/tree/main/UNet3%2B

UNet++: A Nested U-Net Architecture for Medical Image Segmentation

https://github.com/2023-MindSpore-1/ms-code-7/tree/main/ViG

Vision GNN: An Image is Worth Graph of Nodes

https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tinydarknet

Mask R-CNN

https://github.com/2023-MindSpore-1/ms-code-7/tree/main/wave_mlp

An Image Patch is a Wave: Phase-Aware Vision MLP

https://github.com/2023-MindSpore-1/ms-code-7/tree/main/wdsr

Wide Activation for Efficient and Accurate Image Super-Resolution

https://github.com/2023-MindSpore-4/Code-5/tree/main/GhostSR

GhostSR: Learning Ghost Features for Efficient Image Super-Resolution

https://github.com/2023-MindSpore-4/Code-5/tree/main/HRNetW48_cls

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/2023-MindSpore-4/Code-5/tree/main/HiFaceGAN

HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment

https://github.com/2023-MindSpore-4/Code-5/tree/main/HireMLP

Hire-MLP: Vision MLP via Hierarchical Rearrangement

https://github.com/2023-MindSpore-4/Code-5/tree/main/IRN

Invertible Image Rescaling

https://github.com/2023-MindSpore-4/Code-5/tree/main/ISyNet

ISyNet: Convolutional Neural Networks design for AI accelerator

https://github.com/2023-MindSpore-4/Code-5/tree/main/MIMO-UNet

Simple Baselines for Image Restoration

https://github.com/2023-MindSpore-4/Code-5/tree/main/googlenet

Going Deeper with Convolutions

https://github.com/2023-MindSpore-4/Code-5/tree/main/hardnet

HarDNet: A Low Memory Traffic Network

https://github.com/2023-MindSpore-4/Code-5/tree/main/ibnnet

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

https://github.com/2023-MindSpore-4/Code-5/tree/main/lresnet100e_ir

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code-5/tree/main/m2det

M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network

https://github.com/2023-MindSpore-4/Code-5/tree/main/mnasnet

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/2023-MindSpore-4/Code-5/tree/main/mobilenetV3_small_x1_0

Searching for MobileNetV3

https://github.com/2023-MindSpore-4/Code-5/tree/main/mobilenetv3_large

Searching for MobileNetV3

https://github.com/2023-MindSpore-4/Code-5/tree/main/nas-fpn

NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection

https://github.com/2023-MindSpore-4/Code1/tree/main/DeepLabv3

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/2023-MindSpore-4/Code1/tree/main/EDSR

Enhanced Deep Residual Networks for Single Image Super-Resolution

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