目标检测综述

转载连接：目标检测究竟发展到了什么程度? | CVHub带你聊一聊目标检测发展的这22年

详细论文链接和代码可以点开看

[1] Rapid object detection using aboosted cascade of simple features
[2] Histograms of oriented gradients for human detection
[3] A discriminatively trained, multiscale, deformable part model
[4] Rich feature hierarchies for accurate object detection and semantic segmentation
[5] Spatial pyramid pooling in deep convolutional networks for visual recognition
[6] Fast r-cnn
[7] Faster r-cnn: Towards real-time object detection with region proposal networks
[8] Feature pyramid networks for object detection
[9] Cascade R-CNN: Delving into High Quality Object Detection
[10] You only look once: Unified, real-time object detection
[11] SSD: Single shot multibox detector
[12] YOLO9000: better, faster, stronger
[13] Focal loss for dense object detection
[14] Yolov3: An incremental improvement
[15] Yolov4: Optimal speed and accuracy of object detection
[16] Cornernet: Detecting objects as paired keypoints
[17] Centernet: Keypoint triplets for object detection
[18] Feature selective anchor-free module for single-shot object detection
[19] Fcos: Fully convolutional one-stage object detection
[20] Soft Anchor-Point Object Detection