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Found 4 papers, 1 papers with code
Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks
This thesis explore different approaches using Convolutional and Recurrent Neural Networks to classify and temporally localize activities on videos, furthermore an implementation to achieve it has been proposed.
The 2018 DAVIS Challenge on Video Object Segmentation
Motivated by the analysis of the results of the 2017 edition, the main track of the competition will be the same than in the previous edition (segmentation given the full mask of the objects in the first frame -- semi-supervised scenario).
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning
This paper tackles the problem of video object segmentation, given some user annotation which indicates the object of interest.
Ranked #66 on
Semi-Supervised Video Object Segmentation
on DAVIS 2016
The 2019 DAVIS Challenge on VOS: Unsupervised Multi-Object Segmentation
We present the 2019 DAVIS Challenge on Video Object Segmentation, the third edition of the DAVIS Challenge series, a public competition designed for the task of Video Object Segmentation (VOS).
