Papers › Fast Online Object Tracking and Segmentation: A Unifying Approach

Fast Online Object Tracking and Segmentation: A Unifying Approach

12 Dec 2018CVPR 2019 6arXiv:1812.05050archive 2025-07-28

Qiang Wang, Li Zhang, Luca Bertinetto, Weiming Hu, Philip H. S. Torr

In this paper we illustrate how to perform both visual object tracking and semi-supervised video object segmentation, in real-time, with a single simple approach. Our method, dubbed SiamMask, improves the offline training procedure of popular fully-convolutional Siamese approaches for object tracking by augmenting their loss with a binary segmentation task. Once trained, SiamMask solely relies on a single bounding box initialisation and operates online, producing class-agnostic object segmentation masks and rotated bounding boxes at 55 frames per second. Despite its simplicity, versatility and fast speed, our strategy allows us to establish a new state of the art among real-time trackers on VOT-2018, while at the same time demonstrating competitive performance and the best speed for the semi-supervised video object segmentation task on DAVIS-2016 and DAVIS-2017. The project website is http://www.robots.ox.ac.uk/~qwang/SiamMask.

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ezelikman/anonymal mentioned on GitHubpytorchMIT report
foolwood/SiamMask mentioned on GitHubpytorchMIT report
shallowtoil/DROL mentioned on GitHubpytorchApache-2.0 report

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conv3x3 ezelikman/anonymal/experiments/siammask_base/resnet.py community (archive-listed) ran · our draft was wrong MIT (permissive) · fac5364e2f53c6db · report
conv2d_dw_group ezelikman/anonymal/models/rpn.py community (archive-listed) unverified MIT (permissive) · ed07034dd18cfc8f · report
crop_hwc ezelikman/anonymal/datasets/siam_mask_dataset.py community (archive-listed) unverified MIT (permissive) · 3be374ea8fee76b5 · report
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resnet18 ezelikman/anonymal/experiments/siammask_sharp/resnet.py community (archive-listed) unverified MIT (permissive) · 02b73f913b091c75 · report
resnet34 ezelikman/anonymal/experiments/siammask_sharp/resnet.py community (archive-listed) unverified MIT (permissive) · 82928ae508d22d28 · report
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weight_l1_loss ezelikman/anonymal/models/siammask.py community (archive-listed) unverified MIT (permissive) · 27f3175caf7f84b6 · report

Tasks

ObjectObject TrackingReal-Time Visual TrackingSegmentationSemi-Supervised Semantic SegmentationSemi-Supervised Video Object SegmentationVideo Object SegmentationVideo Object TrackingVisual Object TrackingVisual Tracking

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Semi-Supervised Video Object Segmentation DAVIS 2016 SiamMask F-measure (Decay) 2.1 #70 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 SiamMask F-measure (Mean) 67.8 #70 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 SiamMask F-measure (Recall) 79.8 #70 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 SiamMask J&F 69.75 #70 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 SiamMask Jaccard (Decay) 3.0 #70 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 SiamMask Jaccard (Mean) 71.7 #70 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 SiamMask Jaccard (Recall) 86.8 #70 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) SiamMask F-measure (Decay) 22.4 #58 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) SiamMask F-measure (Mean) 45.8 #58 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) SiamMask F-measure (Recall) 45.3 #58 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) SiamMask J&F 43.2 #58 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) SiamMask Jaccard (Decay) 21.9 #58 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) SiamMask Jaccard (Mean) 40.6 #58 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) SiamMask Jaccard (Recall) 44.5 #58 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) SiamMask F-measure (Decay) 20.9 #76 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) SiamMask F-measure (Mean) 58.5 #76 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) SiamMask F-measure (Recall) 67.5 #76 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) SiamMask J&F 56.4 #76 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) SiamMask Jaccard (Decay) 19.3 #76 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) SiamMask Jaccard (Mean) 54.3 #76 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) SiamMask Jaccard (Recall) 62.8 #76 of 81 Archive leaderboard report
Video Object Tracking NT-VOT211 SiamMask AUC 35.14 #22 of 43 Archive leaderboard report
Video Object Tracking NT-VOT211 SiamMask Precision 46.49 #22 of 43 Archive leaderboard report
Visual Object Tracking VOT2017/18 SiamMask Expected Average Overlap (EAO) 0.380 #8 of 15 Archive leaderboard report
Visual Object Tracking YouTube-VOS 2018 SiamMask F-Measure (Seen) 58.2 #3 of 9 Archive leaderboard report
Visual Object Tracking YouTube-VOS 2018 SiamMask F-Measure (Unseen) 47.7 #3 of 9 Archive leaderboard report
Visual Object Tracking YouTube-VOS 2018 SiamMask Jaccard (Seen) 54.3 #3 of 9 Archive leaderboard report
Visual Object Tracking YouTube-VOS 2018 SiamMask Jaccard (Unseen) 45.1 #3 of 9 Archive leaderboard report
Visual Object Tracking YouTube-VOS 2018 SiamMask O (Average of Measures) 52.8 #3 of 9 Archive leaderboard report

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