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/mahdi-darvish/centermask
https://github.com/maiminh1996/YOLOv3-tensorflow
https://github.com/makatx/YOLO_ResNet
https://github.com/makefile/frcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/manankshastri/Object-Detection
https://github.com/manikandan-ravikiran/squeezeDet
https://github.com/manishravula/yolov3_tiny_pruned
https://github.com/marcusnerva/hmn
https://github.com/martinsbruveris/tensorflow-image-models
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/mathieuorhan/darknet
https://github.com/maudzung/CenterNet3D-PyTorch
https://github.com/maudzung/Complex-YOLOv4-Pytorch
https://github.com/maudzung/RTM3D
https://github.com/maudzung/SFA3D
https://github.com/maudzung/YOLO3D-YOLOv4-PyTorch
https://github.com/maudzung/super-fast-accurate-3d-object-detection
https://github.com/maxfrei750/DeepParticleNet
https://github.com/maxfrei750/FibeR-CNN
https://github.com/mayankagarwal44442/Object-Detection-and-localization
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/mayanks888/yolo_custom
https://github.com/mazabou/darknet
https://github.com/mdt48/yolov3-HotelsObjectDetection
https://github.com/mdv3101/darknet-yolov3
https://github.com/meerkatai/Yolo-v4-Object-Detection-Classification
https://github.com/megvii-research/basecls/tree/main/zoo/public/swin
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/meijieru/yet_another_mobilenet_series
MnasNet: Platform-Aware Neural Architecture Search for Mobile
https://github.com/mengyingfei/faster-rcnn-tf
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/miaohua1982/simple_fasterrcnn_pytorch
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/mic-dkfz/medicaldetectiontoolkit
https://github.com/michhar/azureml-keras-yolov3-custom
https://github.com/middleprince/YOLOX-SS
https://github.com/midnight4ever/yolov3
https://github.com/miguelard/cloth_point_cloud_segmentation
https://github.com/mikel-brostrom/Yolov3_DeepSort_Pytorch
https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.