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/saehan-choi/pixellib_auto_labelling
https://github.com/sahadevpoudel/hardnet-mseg
https://github.com/saimj7/Social-Distancing-Detection-in-Real-Time
https://github.com/salman-ghauri/keras_frcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/samirgholipour/speed_estimation
https://github.com/samo1petar/SSD
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/samsh19/ML_project
https://github.com/samson6460/tf2_YOLO
https://github.com/samsonadmin/modified-alexeyab-darknet
https://github.com/sangamdeuja/Helsinki_pedestrian_crossing_detection
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/santhisenan/car-detection-using-yolov2
https://github.com/sara-nl/SURF-deeplab
https://github.com/sara-nl/SURF-segmentation
https://github.com/saransh317/YOLOv3-Easy-Implementation
https://github.com/saumya-jetley/pp_ICVSS15_TacklingBkgndDifferently
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/saurabh241930/yolo_v2_tensorflow
https://github.com/sayakpaul/ConvNeXt-TF
https://github.com/sayakpaul/swin-transformers-tf
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/sbadredd/semantic-pascal-part
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/sbetageri/MaskRCNN
https://github.com/scienXX/roomcamera2
https://github.com/sciosci/graph_check
https://github.com/scolocke/Traffic_Sign_ID_GTSRB_GTSDB
https://github.com/sdkchris/Exercise-Sheet-1
https://github.com/sdu2011/darknet_alexyab
https://github.com/securade/hub
Parallel Detection for Efficient Video Analytics at the Edge
https://github.com/see--/keras-centernet
https://github.com/seongilp/DFE604-2020F-FinalProject
https://github.com/sepuhopar/ReportDD-darknet
https://github.com/sergiosonline/transfercv
https://github.com/sevakon/efficientdet
https://github.com/shanky1947/YOLOv3-Darknet-Custom-Object-Detection
https://github.com/shashigharti/secure-privateai-scholarship-challenge
https://github.com/shellredia/snake-swin-octa
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
https://github.com/shikorab/tf-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.