Gluoncv

\* Using Ground-Truth person detection results

Int8 Quantization with Intel Deep Learning boost

GluonCV is now integrated with Intel's vector neural network instruction(vnni) to accelerate model inference speed.
**Note that you will need a capable Intel Skylake CPU to see proper speed up ratio.**

Model | Dataset | Batch Size | C5.18x FP32 | C5.18x INT8 | Speedup | FP32 Acc | INT8 Acc
-- | -- | -- | -- | -- | -- | -- | --
resnet50_v1 | ImageNet | 128 | 122.02 | 276.72 | 2.27 | 77.21%/93.55% | 76.86%/93.46%

Bug fixes and Improvements

- Now all resnet definitions in GluonCV support Synchronized BatchNorm
- Now pretrained object detection models support `reset_class` for reuse partial category knowledge so some task may not need to finetune models anymore: https://gluon-cv.mxnet.io/build/examples_detection/skip_fintune.html#sphx-glr-build-examples-detection-skip-fintune-py
- Fix some dataloader issue(need mxnet >= 1.4.0)
- Fix some segmentation models that won't hybridize
- Fix some detection model random Nan problems (require mxnet latest nightly build, >= 20190315)
- Various other minor bug fixes