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ラベルなしデータを用いた Dense Tracking の研究事例 / Learning Dense Tracking from Unlabeled Videos

Naoki Kato
August 04, 2020

ラベルなしデータを用いた Dense Tracking の研究事例 / Learning Dense Tracking from Unlabeled Videos

社内勉強会での発表資料です。

ラベルなし動画を用いて画素レベルでのトラッキング(dense tracking)を学習する研究事例を紹介します。

近年では、応用先である Video Object Segmentation において教師あり手法に匹敵する性能を持った教師なし手法が提案されつつあります。

紹介論文:

- Tracking Emerges by Colorizing Videos, ECCV'18
https://arxiv.org/abs/1806.09594

- Learning Correspondence from the Cycle-consistency of Time, CVPR’19
https://arxiv.org/abs/1903.07593

- Unsupervised deep tracking, CVPR’19
https://arxiv.org/abs/1904.01828

- Multigrid Predictive Filter Flow for Unsupervised Learning on Videos, '19
https://arxiv.org/abs/1904.01693

- Self-supervised Learning for Video Correspondence Flow, BMVC’19
https://arxiv.org/abs/1905.00875

- Joint-task Self-supervised Learning for Temporal Correspondence, NeurIPS’19
https://arxiv.org/abs/1909.11895

- MAST: A Memory-Augmented Self-Supervised Tracker, CVPR’20
https://arxiv.org/abs/2002.07793

- Learning Video Object Segmentation from Unlabeled Videos, CVPR’20
https://arxiv.org/abs/2003.05020

- Space-Time Correspondence as a Contrastive Random Walk, ’20
https://arxiv.org/abs/2006.14613

Naoki Kato

August 04, 2020
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    ! %" Video Object Segmentation (VOS) S. Caelles, K.-K. Maninis, J. Pont-Tuset, L. Leal-Taixe, D. Cremers, and L. V. Gool. “One-shot video object segmentation,” In CVPR, 2017.
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    ▪ 1  ▪ & ▪ Region overlapping J&ground-truth #$IoU% ▪ Contour accuracy F&!"F    
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  11. Mobility Technologies Co., Ltd. 12 0DF?M ▪ /A MKineticsK30!*;8005JL ▪

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  21. Mobility Technologies Co., Ltd. ,*& 22 mgPFF [Kong+, ’19] ▪

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  33. Mobility Technologies Co., Ltd. 35 %5 71; ▪ I0 ,

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  34. Mobility Technologies Co., Ltd. 36 Ablation study MAST [Lai+, CVPR’20]

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  37. Mobility Technologies Co., Ltd. 4 QB F@58)", (FCN) =T ▪

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  43. Mobility Technologies Co., Ltd. 46 ▪ Self-supervised  dense tracking

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