Real-Time Object Detection
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Real-Time Object Detection is a computer vision task that involves identifying and locating objects of interest in real-time video sequences with fast inference while maintaining a base level of accuracy.
This is typically solved using algorithms that combine object detection and tracking techniques to accurately detect and track objects in real-time. They use a combination of feature extraction, object proposal generation, and classification to detect and localize objects of interest.
<span style="color:grey; opacity: 0.6">( Image credit: CenterNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ibrahiemhss/android-yolo
https://github.com/idea-research/dab-detr
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
https://github.com/idea-research/dino
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
https://github.com/idea-research/dn-detr
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
https://github.com/idea-research/maskdino
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
https://github.com/ikuokuo/start-scaled-yolov4
https://github.com/ikuto056/Estimating_Distance
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network
https://github.com/imshamsher/darknet
https://github.com/infini8-13/MaskRCNN_tryout
https://github.com/innat/HybridModel-GradCAM
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/innat/VideoSwin
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/insigh/Faster-RCNN-Tensorflow
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/irvankadhafi/Burnt-PCB-Object-Detection
https://github.com/iskandari/darknet
https://github.com/issaiass/FacialMaskDetector
https://github.com/istvanmegyeri/audio_tagging
https://github.com/ithuanhuan/gpu-py3-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/ithuanhuan/py-fatser-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/itsasimiqbal/SeBRe
https://github.com/ivanwhaf/yolov1-pytorch
https://github.com/ivanwilliammd/I3DR-Net-Transfer-Learning
https://github.com/jahongir7174/EfficientDet-tf
https://github.com/jahongir7174/MaskRCNN
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/jalotra/Queue-Detection
https://github.com/jalotra/Queue-Detection-
https://github.com/james128333/HarDNet-MSEG
https://github.com/james77777778/keras-image-models
https://github.com/jasjeetIM/Mask-RCNN
https://github.com/jason-hu7/PyTorch-YOLOv4
https://github.com/jason-su/UCGNet
https://github.com/jayin301/2021AutonomousACCar
https://github.com/jeffshih/autoTrain
PVANet: Lightweight Deep Neural Networks for Real-time Object Detection
https://github.com/jellywangjie/yolov3
https://github.com/jesse01/paddle-yolox
https://github.com/jessychen1016/yolov3Onpytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.