Александр Колесников из IST(http://pub.ist.ac.at/~akolesnikov/)

Title: "Seed, Expand and Constrain: Three Principles for Weakly-Supervised
Image Segmentation"

Abstract: "We introduce a new loss function for the weakly-supervised
training of semantic image segmentation models based on three guiding
principles: to seed with weak location cues, to expand objects based on
the information about which classes can occur, and to constrain the
segmentations to coincide with image boundaries. We show experimentally
that training a deep convolutional neural network using the proposed loss
function leads to substantially better segmentations than previous
state-of-the-art methods on the challenging PASCAL VOC 2012 dataset. We
furthermore give insight into the working mechanism of our method by a
detailed experimental study that illustrates how the segmentation quality
is affected by each term of the proposed loss function as well as their
combinations."

Запись видео скорее всего будет.
Семинары проходят в помещениях ШАД в Яндексе, аудитория Гарвард, начало в 16:30. Приходить можно всем желающим, но если у вас нет пропуска, то нужно заранее написать мне в fb и подойти к торцу здания Тимура Фрунзе 11с5 за 5 минут до начала семинара. Кто планирует ходить постоянно напишите Артему, чтобы запустить процесс создания пропусков (см емейл