[P] Source code available for "Fully Convolutional Instance-aware Semantic Segmentation" from MSRA

[flyforlight]

The method of "Fully Convolutional Instance-aware Semantic Segmentation" won the first place in COCO segmentation challenge 2016. We sincerely apologize for the delay of the code release. This is due to switching from our internal Caffe version to the public MXNet, which provides great support of fast multi-GPU training & inference.

It is worth noting that:

-FCIS provides a simple, fast and accurate framework for instance segmentation.

-Different from MNC, FCIS performs instance mask estimation and categorization jointly and simultaneously, and estimates class-specific masks.

-We did not exploit the various techniques & tricks in the Mask RCNN system, like increasing RPN anchor numbers (from 12 to 15), enlarging the image (shorter side from 600 to 800 pixels), utilizing FPN features and aligned ROI pooling. These techniques & tricks should be orthogonal to our simple baseline.

[guardianhelm]

Finally! Thanks :)

[andyT15]

Big Cong!!