SSD: Single Shot MultiBox Detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg. ECCV 2016.
Models
Using Dataset
| Implementation | Accuracy | Weights | Memory | Conv Ops | etc | Link |
|---|---|---|---|---|---|---|
| Keras | ||||||
| TensorFlow | ||||||
| PyTorch |
Tip & Trick
| name | for What | reference |
|---|---|---|
| Multi-scale featuremap | allow prediction at multiple scales | - |
| Default boxes | allow separately detect objects with different ratio | 'Anchor' in Faster R-CNN |
| jaccard overlay | to get best box | a.k.a. IOU |
| Smooth L1 loss | loss function for bbox regression | image, paper |
| mAP | eval metric | explanation |
| hard negative mining | to sample from a lot of negative boxes | paper |
| a trous algorithm | filling the 'holes' while transforming FC weights into CONV weight | wikipedia |
| NMS(Nom-Max Suppression | to leave only one bbox (with highest confidence level) during inference time | coursera - deep learning |
