Davischallenge.org Website Review

IN-DEPTH AN*LYSIS OF THE STATE-OF-THE-ART IN VIDEO OBJECT SEGMENTATION.   title = {The 2018 DAVIS Challenge on Video Object Segmentation},   journal = {arXiv:1803.00557},   title = {The 2017 DAVIS Challenge on Video Object Segmentation},   journal = {arXiv:1704.00675}, A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation @inproceedings{Perazzi2016,   author = {F. Perazzi and J. Pont-Tuset and B. McWilliams and L. {Van Gool} and M. Gross and A. Sorkine-Hornung},   title = {A Benchmark Dataset and Evaluation Methodology for Video Object Segmentation},   booktitle = {Computer Vision and Pattern Recognition}, Display the evaluation of the current State-of-the-Art segmentation tecniques in DAVIS; using the three presented measures in our work. Visualize the segmentation results for all state-of-the-Art techniques on all DAVIS 2016 images, right from your browser. Do*nload the DAVIS images and annotations, pre-computed results from all techniques, and the code to reproduce the evaluation. It contains the referring expression given the first frame to two annotators in DAVIS 2016 and DAVIS 2017. Moreover, it contains the                 author = {Khoreva, Anna and Rohrbach, Anna and Schiele, Bernt},                 year = {2018},                 booktitle = {As*an Conference on Computer Vision (ACCV)}                 }