Advanced Machine Learning Methodologies for Large-Scale Video Object Segmentation and Detection

  in Special Issue   Posted on November 4, 2020

Information for the Special Issue

Submission Deadline: Tue 01 Dec 2020
Journal Impact Factor : 4.133
Journal Name : IEEE Transactions on Circuits and Systems for Video Technology
Journal Publisher:
Website for the Special Issue: https://zdw-nwpu.github.io/dingwenz.github.com/LOVSD.html
Journal & Submission Website: http://tcsvt.polito.it/

Special Issue Call for Papers:

We welcome all works that are related to the object-oriented video understanding task, including algorithms for segmenting, detecting, tracking, recognizing a certain type of object category, or general object categories in video sequences. Techniques for improving video quality and enhancing feature representation for benefiting the object-oriented video understanding tasks are also within our scope.

Topics of interests include, but are not limited to:

-Video object segmentation/detection based on graph convolutional networks
-Video object segmentation/detection based on capsule networks
-Video object segmentation/detection based on deep reinforcement learning
-Video object segmentation/detection based on generative adversarial learning
-Weakly supervised video object segmentation/detection
-Semi-supervised video object segmentation/detection
-Zero/few-shot video object segmentation/detection
-Unsupervised video object segmentation/detection
-Active learning and cross-domain learning frameworks for video object
segmentation/detection
-Self-taught learning-based frameworks for video object segmentation/detection
-Saliency detection and its applications in video object segmentation/detection
-Representation learning for video object segmentation/detection
-Tracking and other video understanding systems based on video object
segmentation/detection

Closed Special Issues

4.133

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