Papers with Code 아카이브

2D Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

15

평가표

20

보존된 평가 기록

57

코드

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

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-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/HireMLP

Hire-MLP: Vision MLP via Hierarchical Rearrangement

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/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/hed

HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline

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/Efficientnet

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

https://github.com/2023-MindSpore-4/Code10/tree/main/DeepLabv3

Rethinking Atrous Convolution for Semantic Image Segmentation

https://github.com/2023-MindSpore-4/Code10/tree/main/Efficientnet

EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

https://github.com/2023-MindSpore-4/Code10/tree/main/FCOS

FCOS: Fully Convolutional One-Stage Object Detection

https://github.com/2023-MindSpore-4/Code10/tree/main/FasterRCNN

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

https://github.com/2023-MindSpore-4/Code10/tree/main/MaskRCNN

Mask R-CNN

https://github.com/2023-MindSpore-4/Code10/tree/main/ResNet

Deep Residual Learning for Image Recognition

https://github.com/2023-MindSpore-4/Code10/tree/main/RetinaNet

Focal Loss for Dense Object Detection

https://github.com/2023-MindSpore-4/Code10/tree/main/SSD

SSD: Single Shot MultiBox Detector

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