分类、识别论文与项目
Object detection 目标检测 论文与项目。
| Method | VOC2007 | VOC2010 | VOC2012 | ILSVRC 2013 | MSCOCO 2015 | Speed |
|---|---|---|---|---|---|---|
| OverFeat | 24.3% | |||||
| R-CNN (AlexNet) | 58.5% | 53.7% | 53.3% | 31.4% | ||
| R-CNN (VGG16) | 66.0% | |||||
| SPP_net(ZF-5) | 54.2%(1-model), 60.9%(2-model) | 31.84%(1-model), 35.11%(6-model) | ||||
| DeepID-Net | 64.1% | 50.3% | ||||
| NoC | 73.3% | 68.8% | ||||
| Fast-RCNN (VGG16) | 70.0% | 68.8% | 68.4% | 19.7%(@[0.5-0.95]), 35.9%(@0.5) | ||
| MR-CNN | 78.2% | 73.9% | ||||
| Faster-RCNN (VGG16) | 78.8% | 75.9% | 21.9%(@[0.5-0.95]), 42.7%(@0.5) | 198ms | ||
| Faster-RCNN (ResNet-101) | 85.6% | 83.8% | 37.4%(@[0.5-0.95]), 59.0%(@0.5) | |||
| SSD300 (VGG16) | 77.2% | 75.8% | 25.1%(@[0.5-0.95]), 43.1%(@0.5) | 46 fps | ||
| SSD512 (VGG16) | 79.8% | 78.5% | 28.8%(@[0.5-0.95]), 48.5%(@0.5) | 19 fps | ||
| ION | 79.2% | 76.4% | ||||
| CRAFT | 75.7% | 71.3% | 48.5% | |||
| OHEM | 78.9% | 76.3% | 25.5%(@[0.5-0.95]), 45.9%(@0.5) | |||
| R-FCN (ResNet-50) | 77.4% | 0.12sec(K40), 0.09sec(TitianX) | ||||
| R-FCN (ResNet-101) | 79.5% | 0.17sec(K40), 0.12sec(TitianX) | ||||
| R-FCN (ResNet-101),multi sc train | 83.6% | 82.0% | 31.5%(@[0.5-0.95]), 53.2%(@0.5) | |||
| PVANet 9.0 | 89.8% | 84.2% | 750ms(CPU), 46ms(TitianX) |
ICLR 2017 Videos
https://www.facebook.com/pg/iclr.cc/videos/
CVPR’17 Tutorial: Deep Learning for Objects and Scenes