性能对比

2018检测论文

[YOLO v3] YOLOv3: An Incremental Improvement
[ZIP] Zoom Out-and-In Network with Recursive Training for Object Proposal
[SIN] Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships
[STDN] Scale-Transferrable Object Detection
[RefineDet] Single-Shot Refinement Neural Network for Object Detection
[MegDet] MegDet: A Large Mini-Batch Object Detector
[DA Faster R-CNN] Domain Adaptive Faster R-CNN for Object Detection in the Wild
[SNIP] An Analysis of Scale Invariance in Object Detection – SNIP
[Relation-Network] Relation Networks for Object Detection
[Cascade R-CNN] Cascade R-CNN: Delving into High Quality Object Detection
Finding Tiny Faces in the Wild with Generative Adversarial Network
[STDnet] STDnet: A ConvNet for Small Target Detection
[RFBNet] Receptive Field Block Net for Accurate and Fast Object Detection
Zero-Annotation Object Detection with Web Knowledge Transfer
[CornerNet] CornerNet: Detecting Objects as Paired Keypoints
[Pelee] Pelee: A Real-Time Object Detection System on Mobile Devices
[HKRM] Hybrid Knowledge Routed Modules for Large-scale Object Detection
[MetaAnchor] MetaAnchor: Learning to Detect Objects with Customized Anchors
[SNIPER] SNIPER: Efficient Multi-Scale Training

链接：https://github.com/hoya012/deep_learning_object_detection

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