Occluded Video Instance Segmentation With Set Prediction Approach

Heechul Bae, Soonyong Song, Junhee Park; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021, pp. 3850-3853

Abstract

Occluded Video Instance Segmentation (OVIS) is a multi-task problem performing detection, segmentation, and tracking simultaneously under severe occlusions. We propose an extended model for the OVIS task based on the real-time one-stage instance segmentation method. The proposed model was applied to the OVIS dataset hold by the ICCV 2021 - Occluded Video Instance Segmentation Workshop 2021. We also show that the occlusions can be handled efficiently through one-stage approaches.

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[bibtex]
@InProceedings{Bae_2021_ICCV, author = {Bae, Heechul and Song, Soonyong and Park, Junhee}, title = {Occluded Video Instance Segmentation With Set Prediction Approach}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2021}, pages = {3850-3853} }