Papers with Code 아카이브

Object Detection

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

39

평가표

124

보존된 평가 기록

977

코드

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

https://github.com/MS-Mind/MS-Code-06/tree/main/PSPNet

Pyramid Scene Parsing Network

https://github.com/MS-Mind/MS-Code-06/tree/main/pointpillars

https://github.com/MS-Mind/MS-Code-06/tree/main/pointtransformer

Point Transformer

https://github.com/MS-Mind/MS-Code-08/tree/main/MIMO-UNet

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

https://github.com/MS-Mind/MS-Code-08/tree/main/Non_local

Non-local Neural Networks

https://github.com/MS-Mind/MS-Code-08/tree/main/mnasnet

MnasNet: Platform-Aware Neural Architecture Search for Mobile

https://github.com/MS-Mind/MS-Code-08/tree/main/mobilenetV3_small_x1_0

Searching for MobileNetV3

https://github.com/MS-Mind/MS-Code-08/tree/main/mobilenetv3_large

Searching for MobileNetV3

https://github.com/MS-Mind/MS-Code-08/tree/main/nas-fpn

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

https://github.com/MS-P3/code4/tree/main/DECO

DECO: Query-Based End-to-End Object Detection with ConvNets

https://github.com/MS-P3/code4/tree/main/RCNN

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

https://github.com/MS-P3/code4/tree/main/SLAB

SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization

https://github.com/MS-P3/code7/tree/main/vitdet

Aerial Image Object Detection With Vision Transformer Detector (ViTDet)

https://github.com/MS-P3/code7/tree/main/yolos

DETRs Beat YOLOs on Real-time Object Detection

https://github.com/MSJawad/yolov3

YOLOv3: An Incremental Improvement

https://github.com/MSeeker1340/Vision2018-Pose

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

https://github.com/MTCloudVision/mxnet-dssd

SSD: Single Shot MultiBox Detector

https://github.com/MY-Swich/SOLO

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/MY-Swich/SOLO_my

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/MY-Swich/solo-len

SOLOv2: Dynamic and Fast Instance Segmentation

https://github.com/MaczekO/AttentionNetworkProject

Attention Augmented Convolutional Networks

https://github.com/Madave94/VSR-TexBiG-Dataset

https://github.com/Madave94/kalphacv

https://github.com/Madhusakth/Adaptive-Radar-Acquisition

Automotive Radar Data Acquisition using Object Detection

https://github.com/MaheepChaudhary/Stand-Alone_Self-Attention

Stand-Alone Self-Attention in Vision Models

https://github.com/Makunda/DeepLearningASL

Mask R-CNN

https://github.com/Malik1998/VSTAM

https://github.com/ManfredGonzalez/multispectral-pineapple-detection

EfficientDet: Scalable and Efficient Object Detection

https://github.com/ManoniLo/keras-YOLOv3-model-set__Fastest

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/ManooshSamiei/Object-Detection-Deep-Reinforcement-Learning

Object Detection with Deep Reinforcement Learning

https://github.com/Manugoyal12345/Yet-Another-EfficientDet-Pytorch

EfficientDet: Scalable and Efficient Object Detection

https://github.com/Marcos14Almeida/darknet

YOLOv4: Optimal Speed and Accuracy of Object Detection

https://github.com/MargeryLab/Pytorch-UNet-copy

U-Net: Convolutional Networks for Biomedical Image Segmentation

https://github.com/MariefW/6.-trainingYOLO

YOLO9000: Better, Faster, Stronger

https://github.com/MarioNavarrete/anchor_optimization

Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels

https://github.com/Marior87/Telegram_Bot

MobileNetV2: Inverted Residuals and Linear Bottlenecks

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