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Papers › Siam R-CNN: Visual Tracking by Re-Detection

Siam R-CNN: Visual Tracking by Re-Detection

28 Nov 2019CVPR 2020 6arXiv:1911.12836archive 2025-07-28

Paul Voigtlaender, Jonathon Luiten, Philip H. S. Torr, Bastian Leibe

We present Siam R-CNN, a Siamese re-detection architecture which unleashes the full power of two-stage object detection approaches for visual object tracking. We combine this with a novel tracklet-based dynamic programming algorithm, which takes advantage of re-detections of both the first-frame template and previous-frame predictions, to model the full history of both the object to be tracked and potential distractor objects. This enables our approach to make better tracking decisions, as well as to re-detect tracked objects after long occlusion. Finally, we propose a novel hard example mining strategy to improve Siam R-CNN's robustness to similar looking objects. Siam R-CNN achieves the current best performance on ten tracking benchmarks, with especially strong results for long-term tracking. We make our code and models available at www.vision.rwth-aachen.de/page/siamrcnn.

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VisualComputingInstitute/SiamR-CNN tfMIT report

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box_to_point8 VisualComputingInstitute/SiamR-CNN/common.py community (archive-listed) unverified MIT (permissive) · dd749a6b43682a14 · report
freeze_affine_getter VisualComputingInstitute/SiamR-CNN/basemodel.py community (archive-listed) unverified MIT (permissive) · 69d5512d768ea9dd · report
point8_to_box VisualComputingInstitute/SiamR-CNN/common.py community (archive-listed) unverified MIT (permissive) · e99bbed8ef483eba · report
segmentation_to_mask VisualComputingInstitute/SiamR-CNN/common.py community (archive-listed) unverified MIT (permissive) · 72f76b2aba37ad06 · report

Tasks

ObjectObject DetectionObject TrackingSemi-Supervised Video Object SegmentationVisual Object TrackingVisual Trackingobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Object Tracking COESOT SiamR-CNN Precision Rate 67.5 #5 of 12 Archive leaderboard report
Object Tracking COESOT SiamR-CNN Success Rate 60.9 #5 of 12 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 Siam R-CNN F-measure (Decay) 4.0 #63 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 Siam R-CNN F-measure (Mean) 80.4 #63 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 Siam R-CNN F-measure (Recall) 87.6 #63 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 Siam R-CNN J&F 78.6 #63 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 Siam R-CNN Jaccard (Decay) 2.2 #63 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 Siam R-CNN Jaccard (Mean) 76.8 #63 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2016 Siam R-CNN Jaccard (Recall) 86.4 #63 of 78 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) Siam R-CNN F-measure (Decay) 20.2 #50 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) Siam R-CNN F-measure (Mean) 58.6 #50 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) Siam R-CNN F-measure (Recall) 62.3 #50 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) Siam R-CNN J&F 53.3 #50 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) Siam R-CNN Jaccard (Decay) 21.8 #50 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) Siam R-CNN Jaccard (Mean) 48.0 #50 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (test-dev) Siam R-CNN Jaccard (Recall) 53.9 #50 of 59 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) Siam R-CNN F-measure (Decay) 16.2 #60 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) Siam R-CNN F-measure (Mean) 75.0 #60 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) Siam R-CNN F-measure (Recall) 82.8 #60 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) Siam R-CNN J&F 70.55 #60 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) Siam R-CNN Jaccard (Decay) 15.8 #60 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) Siam R-CNN Jaccard (Mean) 66.1 #60 of 81 Archive leaderboard report
Semi-Supervised Video Object Segmentation DAVIS 2017 (val) Siam R-CNN Jaccard (Recall) 74.8 #60 of 81 Archive leaderboard report
Visual Object Tracking GOT-10k Siam R-CNN Average Overlap 64.9 #33 of 42 Archive leaderboard report
Visual Object Tracking GOT-10k Siam R-CNN Success Rate 0.5 72.8 #33 of 42 Archive leaderboard report
Visual Object Tracking LaSOT Siam R-CNN AUC 64.8 #38 of 46 Archive leaderboard report
Visual Object Tracking LaSOT Siam R-CNN Normalized Precision 72.2 #38 of 46 Archive leaderboard report
Visual Object Tracking TrackingNet Siam R-CNN Accuracy 81.2 #28 of 40 Archive leaderboard report
Visual Object Tracking TrackingNet Siam R-CNN Normalized Precision 85.4 #28 of 40 Archive leaderboard report
Visual Object Tracking TrackingNet Siam R-CNN Precision 80.0 #28 of 40 Archive leaderboard report

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