Browse State-of-the-Art › Moving Object Detection
Moving Object Detection
14 papers with code · 1 benchmark · 2 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 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.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| DVSMOTION20 (1 row) | GSCEventMOD | Moving Object Detection for Event-based vision using Graph... | code | — | Compare |
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
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
14 shown of 14 papers with code (70 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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17 Sep 2022 2 repositories listedMoving Object Detection (MOD) is a critical vision task for successfully achieving safe autonomous driving.
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16 May 2025 1 repository listedMTevent is the first dataset to combine high-speed motion, long-range perception, and real-world object interactions, making it a valuable resource for advancing event-based vision in robotics.
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25 Apr 2025 1 repository listedEvent cameras provide rich signals that are suitable for motion estimation since they respond to changes in the scene.
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24 Nov 2024 1 repository listedSpecifically, we propose a generic unsupervised framework for SVMOD, in which pseudo labels generated by a traditional method can evolve with the training process to promote detection performance.
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11 Aug 2024 1 repository listedFalling objects from buildings can cause severe injuries to pedestrians due to the great impact force they exert.
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18 Sep 2023 1 repository listedMobile autonomy relies on the precise perception of dynamic environments.
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25 Nov 2021 1 repository listedSatellite video cameras can provide continuous observation for a large-scale area, which is important for many remote sensing applications.
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19 Oct 2021 1 repository listedWide Area Motion Imagery (WAMI) yields high-resolution images with a large number of extremely small objects.
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30 Sep 2021 1 repository listedHowever, these advantages come at a high cost, as the event camera data typically contains more noise and has low resolution.
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4 Sep 2021 1 repository listedMoving object detection is important in computer vision.
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21 Mar 2021 1 repository listedThe problem of recognizing moving objects from aerial images is one of the important issues in computer vision.
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15 Dec 2020 1 repository listedCompared to other methods, such as deblatting, the inference is of several orders of magnitude faster and allows applications such as real-time fast moving object detection and retrieval in large video collections.
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11 Feb 2019 1 repository listedTo address this concern, we propose two new benchmarks for generic, moving object detection, and show that our model matches top-down methods on common categories, while significantly out-performing both top-down and…
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10 Jan 2019 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedWe propose an adversarial contextual model for detecting moving objects in images.
Syntology lines on 1 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.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections