Occluded Video Instance Segmentation with Set Prediction Approach

被引：0
|
作者：
Bae, Heechul [1 ]
Song, Soonyong [1 ]
Park, Junhee [1 ]
机构：
[1] Elect & Telecommun Res Inst ETRI, Ind & IoT Intelligence Res Dept, Daejeon, South Korea
来源：
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021) | 2021年
关键词：
D O I：
10.1109/ICCVW54120.2021.00429
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：3843 / 3846
页数：4
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