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/zhaott618/centernet_codes_notes
https://github.com/zhechen/deformable-detr-rego
Deformable DETR: Deformable Transformers for End-to-End Object Detection
https://github.com/zhiqwang/crnn.pytorch
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/zhiqwang/image-captioning
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/zhong110020/py-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/zhongzisha/object_detection
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/zhreshold/mxnet-yolo
https://github.com/zhuMingXu/rearHeadLightDetection
https://github.com/zhudelong/elevator_button_recognition
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/zhuoyang125/CenterMask2
https://github.com/zibbini/convnext-v2_tensorflow
https://github.com/zj463261929/darknet_mAP
https://github.com/zjZSTU/YOLO_v1
https://github.com/zjjszj/yolov3
https://github.com/zoeShao/CSC420-Project
https://github.com/zxhuang97/Official-implementation-StyleMixer
https://github.com/zxqcreations/faster-rcnn-tf
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch
https://github.com/zzdxfei/defor_conv_mxnet_code
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/zzfpython/yolov3-change
https://github.com/zzh8829/yolov3-tf2
https://github.com/zzhuolun/IRL
https://gitlab.com/birder/birder
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://gitlab.com/eavise/lightnet
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.