Research Project

website: https://github.com/rbgirshick/py-faster-rcnn $PloygonRNN$ = /Lab/projects/Python/polyrnn$ $ python $ conda create -n my_env python=2.7 anaconda $ source activate my_env $ pip install -r requirements.txt error(may affect the later use): grin 1.2.1 requires argparse>=1.1, which is not installed.

## 1. Deep extreme cut: From extreme points to object segmentation, Kevis et al_ CVPR2018 ##    (1) paper and code     paper link: https://arxiv.org/abs/1711.09081     code(pytorch):  https://github.com/scaelles/DEXTR-PyTorch     (website) [ http://people.ee.ethz.ch/~cvlsegmentation/dextr/ ]    (2) problem range     target:  single image testing datasets: COCO, Pascal VOC, GrabCut, Davis 2016, Davis 2017 (3) architecture     (inference) input: four extreme points(left-most, right-most, top and bottom)     (refinement)input: the above four points+   one extra point    (4)Implement details:    Balance loss(cross-entropy)    (5) results:    1> Obtaining state-of-the-art results in all scenarios.    2> Reducing labeling costs by a factor of 10. ##================================================== ## ## 2. Annot...