Browse State-of-the-Art › Visual Tracking
Visual Tracking
202 papers with code · 10 benchmarks · 28 datasets archive 2025-07-28
Visual Tracking is an essential and actively researched problem in the field of computer vision with various real-world applications such as robotic services, smart surveillance systems, autonomous driving, and human-computer interaction. It refers to the automatic estimation of the trajectory of an arbitrary target object, usually specified by a bounding box in the first frame, as it moves around in subsequent video frames.
Source: Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
10 leaderboard tables shown for this task, 10 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
28 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
4 subtasks in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 202 papers with code (525 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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31 Dec 2018 13 repositories listed Syntology ran 3 of 17 samples · 14 unverifiedMoreover, we propose a new model architecture to perform depth-wise and layer-wise aggregations, which not only further improves the accuracy but also reduces the model size.
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17 May 2017 11 repositories listedRobust object tracking requires knowledge and understanding of the object being tracked: its appearance, its motion, and how it changes over time.
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14 Nov 2019 6 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)Following these guidelines, we design our Fully Convolutional Siamese tracker++ (SiamFC++) by introducing both classification and target state estimation branch(G1), classification score without ambiguity(G2), tracking…
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7 Jan 2019 5 repositories listed Syntology ran 3 of 3 samples · 0 unverifiedSiamese networks have drawn great attention in visual tracking because of their balanced accuracy and speed.
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1 Jun 2018 5 repositories listedVisual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks.
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13 Apr 2017 5 repositories listedIn this work, we present an end-to-end lightweight network architecture, namely DCFNet, to learn the convolutional features and perform the correlation tracking process simultaneously.
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9 Mar 2024 4 repositories listedCurrent event-/frame-event based trackers undergo evaluation on short-term tracking datasets, however, the tracking of real-world scenarios involves long-term tracking, and the performance of existing tracking…
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26 Sep 2023 4 repositories listed Syntology ran 9 of 9 samples · 0 unverified · 9 pointer-only (licence)Tracking using bio-inspired event cameras has drawn more and more attention in recent years.
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7 Feb 2019 4 repositories listedIt combines a Convolutional Neural Network (CNN) backbone and a cross-correlation operator, and takes advantage of the features from exemplary images for more accurate object tracking.
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19 Nov 2018 4 repositories listed Syntology ran 3 of 9 samples · 6 unverifiedWe argue that this approach is fundamentally limited since target estimation is a complex task, requiring high-level knowledge about the object.
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14 Jun 2023 3 repositories listed Syntology ran 0 of 1 samples · 1 unverifiedWe present a novel model for Tracking Any Point (TAP) that effectively tracks any queried point on any physical surface throughout a video sequence.
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12 Dec 2018 3 repositories listed Syntology ran 1 of 10 samples · 9 unverifiedIn 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.
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12 Sep 2018 3 repositories listedCompared with short-term tracking, the long-term tracking task requires determining the tracked object is present or absent, and then estimating the accurate bounding box if present or conducting image-wide re-detection…
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27 Aug 2018 3 repositories listedWe present a fast and accurate visual tracking algorithm based on the multi-domain convolutional neural network (MDNet).
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12 Sep 2017 3 repositories listedCross-correlator plays a significant role in many visual perception tasks, such as object detection and tracking.
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22 Jul 2024 2 repositories listed Syntology ran 6 of 12 samples · 6 unverifiedWe introduce LocoTrack, a highly accurate and efficient model designed for the task of tracking any point (TAP) across video sequences.
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28 May 2024 2 repositories listedTechnically, we achieve this by routing samples from one modality to the expert of the others, within a mixture-of-experts framework designed for multimodal video object tracking.
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6 Mar 2024 2 repositories listedThe rich annotations of VastTrack enables development of both the vision-only and the vision-language tracking.
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21 Mar 2022 2 repositories listedWe infer a bounding box from the segmentation mask, validate our tracker on challenging tracking datasets and achieve the new state of the art on LaSOT with a success AUC score of 69.
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30 Jan 2022 2 repositories listed Syntology ran 4 of 30 samples · 26 unverifiedThe canonical object representation is learned solely in simulation and then used to parse a category-level, task trajectory from a single demonstration video.
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28 Dec 2021 2 repositories listedIn this paper, we propose a simple yet effective recursive least-squares estimator-aided online learning approach for few-shot online adaptation without requiring offline training.
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17 Dec 2021 2 repositories listedE.
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13 Dec 2021 2 repositories listedOur objective is to locate and provide a unique identifier for each mouse in a cluttered home-cage environment through time, as a precursor to automated behaviour recognition for biological research.
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31 Mar 2021 2 repositories listedWe believe this benchmark will greatly boost related researches on natural language guided tracking.
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8 Mar 2021 2 repositories listedAs a crucial robotic perception capability, visual tracking has been intensively studied recently.
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8 Dec 2020 2 repositories listedVisual object tracking, as a fundamental task in computer vision, has drawn much attention in recent years.
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4 May 2020 2 repositories listed Syntology ran 0 of 3 samples · 3 unverifiedWhile they are commonly employed for generative image modeling, recent work has applied EBMs also for regression tasks, achieving state-of-the-art performance on object detection and visual tracking.
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15 Apr 2020 2 repositories listedTo tackle this issue, we present the fully convolutional online tracking framework, coined as FCOT, and focus on enabling online learning for both classification and regression branches by using a target filter based…
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1 Apr 2020 2 repositories listedMost top-ranked long-term trackers adopt the offline-trained Siamese architectures, thus, they cannot benefit from great progress of short-term trackers with online update.
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27 Mar 2020 2 repositories listedIn this work, we therefore propose a probabilistic regression formulation and apply it to tracking.
Syntology lines on 10 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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