Papers with Code 아카이브
Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/ryosuke-yamada/3dfractaldb
https://github.com/ryota2425/maskrcnn-benchmark
RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free
https://github.com/ryubidragonfire/mydarknet
https://github.com/s-a-malik/multi-few
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/s0ntr4n97/datasets
https://github.com/s1ns11/FasterR-CNN
Rich feature hierarchies for accurate object detection and semantic segmentation
https://github.com/s1r2ikanth/Atunomous-Driving-Application--For-Car-detection
https://github.com/s9mondal9upriti/U-Net
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/saadbutt32/Conversion-of-Pakistan-Sign-Languag-into-Text-and-Speech-using-OpenPose-and-Machine-Learning
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/saadbutt32/Pakistan-Sign-Language-Interpreter
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/sabadijou/byol_multi_gpu
https://github.com/sabadijou/clld_official
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/saber2011/darknet
https://github.com/sabrisangjaya/plantdoctor
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/sacmehta/espnetv2-coreml
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
https://github.com/sadari1/TumorDetectionDeepLearning
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/sadicLiu/darknet
https://github.com/sadicLiu/darknet-yolov4
https://github.com/sadicLiu/mask_rcnn_code
RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free
https://github.com/sadicLiu/yolov3
https://github.com/saednasir/Helmet_Yolo
https://github.com/saehan-choi/pixellib_auto_labelling
https://github.com/sagar-barapatre/Image-Classifier
https://github.com/saghiralfasly/SynthBRSet
OSRE: Object-to-Spot Rotation Estimation for Bike Parking Assessment
https://github.com/saghiralfasly/VFL-Vehicle-Re-Id
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
https://github.com/sagnik1511/U-Net-Reduced-with-TF-keras
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/sagnik1511/U-Net-Reduced-with-keras
U-Net: Convolutional Networks for Biomedical Image Segmentation
https://github.com/sahadevpoudel/hardnet-mseg
https://github.com/sahamath/SYM-Net
LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence
https://github.com/sahamath/sym-netv1
LipschitzLR: Using theoretically computed adaptive learning rates for fast convergence
https://github.com/sahilkhose/FloodNet
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
https://github.com/sahilkhose/floodnet_vqa
FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
https://github.com/saikrishnadas/ResNet-Pytorch
https://github.com/sailfish009/detectron2-ResNeSt
https://github.com/sailist/thexp-implement
RandAugment: Practical automated data augmentation with a reduced search space
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.