Task type	Topology name	Framework	Dataset	Accuracy type	OpenVINO DLDT CPU FP32 INT8 GPU FP32 FP16 INT8 MYRIAD FP16
classification	alexnet caffenet densenet-121 densenet-121-tf hbonet-0.25 efficientnet-b0 efficientnet-b0-pytorch googlenet-v1 googlenet-v2 googlenet-v3 googlenet-v3-pytorch googlenet-v4-tf googlenet-v1-tf inception-resnet-v2-tf mobilenet-v1-0.25-128 mobilenet-v1-1.0-224 mobilenet-v1-1.0-224-tf mobilenet-v2 mobilenet-v2-pytorch mobilenet-v2-1.4-224 mobilenet-v2-1.0-224 resnet-50-tf resnet-50-pytorch resnet-18-pytorch se-inception se-resnet-101 se-resnet-152 squeezenet1.0 squeezenet1.1 vgg16 vgg19 googlenet-v2-tf mobilenet-v3-large-1.0-224-tf mobilenet-v3-small-1.0-224-tf octave-resnet-26-0.25 pelee-coco	Caffe Caffe Caffe TensorFlow TensorFlow TensorFlow PyTorch Caffe Caffe TensorFlow PyTorch TensorFlow TensorFlow TensorFlow TensorFlow Caffe TensorFlow Caffe PyTorch TensorFlow TensorFlow TensorFlow PyTorch PyTorch Caffe Caffe Caffe Caffe Caffe Caffe Caffe TensorFlow TensorFlow TensorFlow MXNet Caffe	ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet N/A N/A ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet ImageNet N/A N/A	accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 N/A N/A accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 accuracy@top1 accuracy@top5 N/A N/A	56.60% 79.81% 56.51% 79.67% 56.72% 79.91% 56.65% 79.82% 74.41% 92.14% 74.07% 91.87% 74.47% 92.13% 74.01% 91.82% 57.38% 79.86% 52.97% 76.20% 75.69% 92.76% 73.68% 91.72% 76.91% 93.21% 75.86% 92.62% 68.92% 89.14% 68.68% 89.03% 72.03% 90.86% 71.98% 90.87% 77.89% 93.80% 77.88% 93.80% 77.69% 93.70% 77.61% 93.62% 80.21% 95.20% 80.17% 95.19% 69.81% 89.61% 69.89% 89.56% 77.82% 94.03% 77.70% 93.99% 41.55% 66.35% 39.60% 64.19% 69.49% 89.24% 69.17% 88.98% 71.11% 89.88% 70.82% 89.79% 71.23% 90.18% 69.82% 89.37% 71.88% 90.30% 71.20% 90.02% 74.88% 92.36% 74.13% 91.97% 71.85% 90.69% 70.83% 89.89% 76.44% 93.07% 76.40% 93.01% 76.13% 92.86% 75.87% 92.81% 69.76% 89.08% 69.40% 88.97% 75.99% 92.97% 75.79% 92.82% N/A N/A N/A N/A 57.67% 80.39% 57.14% 80.18% 58.38% 81.01% 57.87% 80.89% 70.96% 89.88% 70.90% 89.86% 71.06% 89.83% 71.04% 89.82% 74.09% 91.80% 73.89% 91.73% 72.54% 91.45% 51.70% 76.11% 56.79% 81.25% 51.71% 77.38% N/A N/A N/A N/A 56.60% 79.81% 56.61% 79.82% 56.51% 79.67% 56.72% 79.91% 56.69% 79.93% 56.65% 79.82% 74.41% 92.14% 74.48% 92.12% 74.07% 91.87% 74.47% 92.13% 74.47% 92.13% 74.01% 91.82% 57.38% 79.86% 57.37% 79.83% 52.97% 76.20% 75.69% 92.76% 75.74% 92.77% 73.68% 91.72% 76.91% 93.21% 76.94% 93.23% 75.86% 92.62% 68.92% 89.14% 68.93% 89.14% 68.68% 89.03% 72.03% 90.86% 71.98% 90.83% 71.98% 90.87% 77.89% 93.80% 77.90% 93.81% 77.88% 93.80% 77.69% 93.70% 77.67% 93.69% 77.61% 93.62% 80.21% 95.20% 80.20% 95.22% 80.17% 95.19% 69.81% 89.61% 69.82% 89.57% 69.89% 89.56% 77.82% 94.03% 77.81% 94.03% 77.70% 93.99% 41.55% 66.35% 41.49% 66.34% 39.60% 64.19% 69.49% 89.24% 69.50% 89.24% 69.17% 88.98% 71.11% 89.88% 71.06% 89.87% 70.82% 89.79% 71.23% 90.18% 71.21% 90.22% 69.82% 89.37% 71.88% 90.30% 71.90% 90.30% 71.20% 90.02% 74.88% 92.36% 74.90% 92.37% 74.13% 91.97% 71.85% 90.69% 71.83% 90.68% 70.83% 89.89% 76.44% 93.07% 76.44% 93.09% 76.40% 93.01% 76.13% 92.86% 76.10% 92.86% 75.87% 92.81% 69.76% 89.08% 69.71% 89.08% 69.40% 88.97% 75.99% 92.97% 75.99% 92.94% 75.79% 92.82% N/A N/A N/A N/A N/A N/A 57.67% 80.39% 71.00% 89.88% 57.14% 80.18% 58.38% 81.01% 71.07% 89.84% 57.87% 80.89% 70.96% 89.88% 56.47% 79.57% 70.90% 89.86% 71.06% 89.83% 76.38% 93.18% 71.04% 89.82% 74.09% 91.80% 67.33% 87.42% 73.89% 91.73% 72.54% 91.45% 76.09% 92.99% 51.70% 76.11% 56.79% 81.25% 76.07% 92.58% 51.71% 77.38% N/A N/A N/A N/A N/A N/A 56.59% 79.79% 56.75% 79.91% 74.46% 92.12% 74.50% 92.08% 57.30% 79.79% 74.19% 91.94% 76.91% 93.17% 68.92% 89.12% 72.00% 90.75% 76.90% 93.33% 77.72% 93.68% 79.06% 94.49% 69.84% 89.60% 75.29% 92.72% 41.34% 66.22% 69.44% 89.17% 71.07% 89.85% 71.24% 90.19% 71.64% 90.28% 74.43% 92.12% 71.82% 90.63% 76.46% 93.01% 76.08% 92.87% 69.72% 89.07% 76.02% 92.94% N/A N/A 70.94% 89.84% 71.09% 89.82% 56.48% 79.56% 76.40% 93.08% 67.22% 87.38% 76.08% 92.94% 76.01% 92.48% N/A N/A
semantic segmentation	deeplabv3	TensorFlow	VOC2012	mean_iou	68.41% N/A 68.41% 66.83% N/A 66.84%
instance segmentation	mask_rcnn_inception_resnet_v2_atrous_coco mask_rcnn_resnet50_atrous_coco	TensorFlow TensorFlow	MS COCO MS COCO	coco_orig_precision coco_orig_segm_precision coco_orig_precision coco_orig_segm_precision	39.86% 35.36% N/A N/A 29.74% 27.45% N/A N/A 39.86% 35.36% 39.86% 35.38% N/A N/A 29.74% 27.45% 29.84% 27.53% N/A N/A N/A N/A N/A N/A
object detection	faster_rcnn_inception_resnet_v2_atrous_coco faster_rcnn_resnet50_coco	TensorFlow TensorFlow	MS COCO MS COCO	coco_precision coco_precision	40.69% N/A 31.10% N/A N/A 40.61% N/A N/A 31.10% N/A N/A 31.09%
detection	ssd300 ssd512 mobilenet-ssd ssd_mobilenet_v1_fpn_coco ssd_mobilenet_v2_coco yolo-v1-tiny-tf yolo-v2-tiny-tf yolo-v2-tf yolo-v3-tf	Caffe Caffe Caffe TensorFlow TensorFlow TensorFlow.js Keras Keras Keras	PASCAL VOC PASCAL VOC PASCAL VOC MS COCO MS COCO PASCAL VOC MS COCO MS COCO MS COCO	map map map coco_precision coco_precision map coco_precision map coco_precision map coco_precision map	85.08% N/A 90.39% N/A 79.84% N/A 35.56% N/A 24.95% N/A 72.16% N/A 29.11% 27.35% N/A N/A 56.50% 53.15% N/A N/A 67.70% 62.30% N/A N/A N/A 85.07% N/A N/A 90.39% N/A N/A 66.73% N/A 35.56% 35.61% N/A 24.95% 24.94% N/A N/A 72.16% N/A N/A N/A 29.11% 27.35% N/A N/A N/A N/A 56.40% 53.14% N/A N/A N/A N/A N/A N/A N/A N/A 85.07% 90.39% 66.73% 35.61% 24.94% 72.16% 29.11% 27.35% 56.40% 53.14% N/A N/A