Browse State-of-the-Art › Vehicle Pose Estimation
Vehicle Pose Estimation
20 papers with code · 4 benchmarks · 4 datasets archive 2025-07-28
Image Credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision, ECCV'20
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
4 leaderboard tables shown for this task, 4 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 |
|---|---|---|---|---|---|
| KITTI Cars Hard (19 rows) | Ego-Net (Monocular RGB only) | Exploring intermediate representation for monocular vehicle pose estimation | code | — | Compare |
| ApolloCar3D (1 row) | GSNet | GSNet: Joint Vehicle Pose and Shape Reconstruction with... | code | — | Compare |
| KITTI (1 row) | Ego-Net | Exploring intermediate representation for monocular vehicle pose estimation | code | — | Compare |
| CarFusion (1 row) | Occlusion-NET | Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks | 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
4 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
20 shown of 20 papers with code (37 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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1 Dec 2016 11 repositories listed Syntology ran 3 of 27 samples · 24 unverified · 5 pointer-only (licence)In contrast to current techniques that only regress the 3D orientation of an object, our method first regresses relatively stable 3D object properties using a deep convolutional neural network and then combines these…
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13 Jul 2019 4 repositories listed Syntology ran 1 of 21 samples · 20 unverifiedUnderstanding the world in 3D is a critical component of urban autonomous driving.
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29 Nov 2023 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)Traditional 2D pose estimation models are limited by their category-specific design, making them suitable only for predefined object categories.
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19 Jul 2020 2 repositories listed Syntology ran 3 of 20 samples · 17 unverifiedIn this work, we propose a novel method for monocular video-based 3D object detection which carefully leverages kinematic motion to improve precision of 3D localization.
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10 Jan 2020 2 repositories listed Syntology ran 6 of 16 samples · 10 unverifiedDifferent from these approaches, our method predicts the nine perspective keypoints of a 3D bounding box in image space, and then utilize the geometric relationship of 3D and 2D perspectives to recover the dimension,…
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10 Dec 2019 2 repositories listed Syntology ran 2 of 16 samples · 14 unverified3D object detection from a single image without LiDAR is a challenging task due to the lack of accurate depth information.
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1 Jun 2024 1 repository listedWe validate our novel approach using the MP-100 benchmark, a comprehensive dataset spanning over 100 categories and 18, 000 images.
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2 Feb 2023 1 repository listedIn this paper, we propose a novel vehicle pose estimation method based on the convex hull.
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24 Jun 2022 1 repository listedWe consider an active shape model, where -- for an object category -- we are given a library of potential CAD models describing objects in that category, and we adopt a standard formulation where pose and shape are…
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16 Apr 2021 1 repository listedOur first contribution is to provide the first certifiably optimal solver for pose and shape estimation.
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17 Nov 2020 1 repository listedThe latter question motivates us to incorporate geometry knowledge with a new loss function based on a projective invariant.
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26 Jul 2020 1 repository listedGSNet utilizes a unique four-way feature extraction and fusion scheme and directly regresses 6DoF poses and shapes in a single forward pass.
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7 Apr 2020 1 repository listed Syntology ran 3 of 3 samples · 0 unverifiedIn this paper, we propose a novel system named Disp R-CNN for 3D object detection from stereo images.
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1 Mar 2020 1 repository listedMonocular 3D object detection is an essential component in autonomous driving while challenging to solve, especially for those occluded samples which are only partially visible.
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10 Jan 2020 1 repository listed Syntology ran 1 of 5 samples · 4 unverifiedMost state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods.
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15 Jun 2019 1 repository listedWe present a conceptually simple framework for 6DoF object pose estimation, especially for autonomous driving scenario.
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1 Jun 2019 1 repository listedCentral to this work is a trifocal tensor loss that provides indirect self-supervision for occluded keypoint locations that are visible in other views of the object.
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2 Apr 2019 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)We present MonoPSR, a monocular 3D object detection method that leverages proposals and shape reconstruction.
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2 Mar 2017 1 repository listedWe also show that our method outperforms the state-of-the-art methods for fine-grained recognition.
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16 Apr 2016 1 repository listedIn CNN-based object detection methods, region proposal becomes a bottleneck when objects exhibit significant scale variation, occlusion or truncation.
Syntology lines on 9 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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