CSPDarknet53 is a convolutional neural network and backbone for object detection that uses DarkNet-53. It employs a CSPNet strategy to partition the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use of a split and merge strategy allows for more gradient flow through the network.
This CNN is used as the backbone for YOLOv4.
Source: YOLOv4: Optimal Speed and Accuracy of Object DetectionPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
---|---|---|
Object Detection | 73 | 32.02% |
Real-Time Object Detection | 15 | 6.58% |
Autonomous Driving | 7 | 3.07% |
Semantic Segmentation | 6 | 2.63% |
Object Tracking | 6 | 2.63% |
2D Object Detection | 6 | 2.63% |
Multi-Object Tracking | 5 | 2.19% |
Instance Segmentation | 4 | 1.75% |
Multiple Object Tracking | 4 | 1.75% |