Object detection has been widely applied in various fields with the rapid development of deep learning in recent years. However, detecting small objects is still a challenging task because of the limited inform
The object scale of a small object scene changes greatly, and the object is easily disturbed by a complex background. Generic object detectors do not perform well on small object detection tasks. In this paper, we focus on small object detection based on
we systematically study various neural network architecture design choices for object detection and propose several key optimizations to improve efficiency. First, we propose a weightedbi-directional feature pyramid network(BiFPN), which allows easy andfast multi-scale feature fusion; Second, we propose ...
Average Precision IoU=0.50:0.95 area= small maxDets=100 0.093 Average Precision IoU=0.50:0.95 area= medium maxDets=100 0.358 Average Precision IoU=0.50:0.95 area= large maxDets=100 0.517 Average Recall IoU=0.50:0.95 area= all maxDets=1 0.268 Average Recall IoU=0.50:0.95 area= all maxDets=10 ...
throughafineleveldetectorwhenitisdominatedbysmall objects.Thisreducesthedependencyonhighspatialreso- lutionimagesforbuildingarobustdetectorandincreases run-timeefficiency.WeperformexperimentsonthexView dataset,consistingoflargeimages,whereweincreaserun- timeefficiencyby50%andusehighresolutionimagesonly ...
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DFS-DETR: Detailed-Feature-Sensitive Detector for Small Object Detection in Aerial Images Using Transformer This paper addresses the critical need for accurate and efficient object detection in aerial images using a Transformer-based approach enhanced with specialized... X Cao,H Wang,X Wang,... -...
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Efficient Teacher introduces semi-supervised object detection into practical applications, enabling users toobtain a strong generalization capability with only a small amount of labeled data and large amount of unlabeled data. Efficient Teacher provides category and custom uniform sampling, which can quickly...
2015-NIPS-Structured Transforms for Small-Footprint Deep Learning 2015-NIPS-Tensorizing Neural Networks 2015-NIPSw-Distilling Intractable Generative Models 2015-NIPSw-Federated Optimization:Distributed Optimization Beyond the Datacenter 2015-CVPR-Efficient and Accurate Approximations of Nonlinear Convolutional Netw...