https://github.com/ginn24/Pelee-TensorRT
Pelee: A Real-Time Object Detection System on Mobile Devices
Papers with Code 아카이브
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/gitting-it-right/gaussian_centernet
https://github.com/gloria111/YOLOX_paddle
https://github.com/glouppe/info8010-deep-learning
https://github.com/godspeedcurry/lung-nodule-detection
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/gokulkarthik/deformable-detr
Deformable DETR: Deformable Transformers for End-to-End Object Detection
https://github.com/gokulprasadthekkel/pytorch-multi-class-focal-loss
https://github.com/gomboskriszta/yolo
https://github.com/goodxue/CenterNet
https://github.com/google/automl/tree/master/efficientdet
https://github.com/goswal/Pothole-Detection-Using-Deep-Learning-and-Computer-Vision
https://github.com/gouthamvgk/coreml_conversion_hub
https://github.com/gpandu/Object-detection
https://github.com/gpandu/YOLO2_ObjectDetection
https://github.com/gplast/DroNet
DroNet: Efficient convolutional neural network detector for real-time UAV applications
https://github.com/gplast/DroNet_PyTorch
DroNet: Efficient convolutional neural network detector for real-time UAV applications
https://github.com/guagen/yolov3-ultralytics-source
https://github.com/guanfuchen/Deformable-ConvNets
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/guanfuchen/py-faster-rcnn
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/gunooknam/Code_Study_Yolov3
https://github.com/guxiaowei1/yolov3--detection-of-rmb-code-region
https://github.com/gyes00205/waymo_tf_object_detection
https://github.com/gzerveas/gaila_object_detection
https://github.com/gzw820/PyTorch_YOLOv4
https://github.com/hades12580/centermask2
https://github.com/haithink/myWindowsDarknet
https://github.com/hamidriasat/-Computer-Vision-and-Deep-Learning
https://github.com/hamidriasat/Computer-Vision-and-Deep-Learning
https://github.com/hamzaMahdi/darknet
https://github.com/hanfried/hanfried-bookmarks
https://github.com/hanghang177/pedestrian_awareness
https://github.com/hankpark0706/darknet
https://github.com/hanouticelina/deformable-DETR
Deformable DETR: Deformable Transformers for End-to-End Object Detection
https://github.com/haoy945/demf
Deformable DETR: Deformable Transformers for End-to-End Object Detection
https://github.com/harinath0906/Object-Detection-using-PyTorch
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
https://github.com/harinath0906/Wheat-Head-Detection-using-PyTorch
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.