Browse State-of-the-Art › Viewpoint Estimation
Viewpoint Estimation
17 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
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
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
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Most implemented papers archive 2025-07-28
17 shown of 17 papers with code (41 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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21 May 2015 4 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)Object viewpoint estimation from 2D images is an essential task in computer vision.
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23 Jul 2020 2 repositories listed Syntology ran 1 of 17 samples · 16 unverifiedIn this paper, we tackle the problems of few-shot object detection and few-shot viewpoint estimation.
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15 Jul 2020 2 repositories listedIn this paper, we investigate when and how such OOD generalization may be possible by evaluating CNNs trained to classify both object category and 3D viewpoint on OOD combinations, and identifying the neural mechanisms…
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3 Apr 2020 2 repositories listedTraining deep neural networks to estimate the viewpoint of objects requires large labeled training datasets.
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12 Jun 2019 2 repositories listed Syntology ran 1 of 11 samples · 10 unverifiedMost deep pose estimation methods need to be trained for specific object instances or categories.
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10 Apr 2019 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)We observe many continuous output problems in computer vision are naturally contained in closed geometrical manifolds, like the Euler angles in viewpoint estimation or the normals in surface normal estimation.
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3 Sep 2018 2 repositories listedIn this work, we propose a data-efficient method which utilizes the geometric regularity of intraclass objects for pose estimation.
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3 Aug 2018 2 repositories listedSuch image comparison based approach also alleviates the problem of data scarcity and hence enhances scalability of the proposed approach for novel object categories with minimal annotation.
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7 Jan 2024 1 repository listedWe present See360, which is a versatile and efficient framework for 360 panoramic view interpolation using latent space viewpoint estimation.
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12 May 2021 1 repository listedWe experimented on Pascal3D+, ObjectNet3D and Pix3D in a cross-dataset fashion, with both seen and unseen classes.
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16 Sep 2020 1 repository listedMany vision tasks use secondary information at inference time -- a seed -- to assist a computer vision model in solving a problem.
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5 Jun 2020 1 repository listedOur key insight is that although we do not have an explicit 3D model or a predefined canonical pose, we can still learn to estimate the object's shape in the viewer's frame and then use an image to provide our reference…
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17 Oct 2019 1 repository listedWe present a convolutional neural network for joint 3D shape prediction and viewpoint estimation from a single input image.
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12 Apr 2018 1 repository listedWe study 3D shape modeling from a single image and make contributions to it in three aspects.
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25 Mar 2018 1 repository listedExisting methods define semantic keypoints separately for each category with a fixed number of semantic labels in fixed indices.
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5 Feb 2018 1 repository listedWe address this question by formulating it as an Adviser Problem: can we learn a mapping from the input to a specific question to ask the human to maximize the expected positive impact to the overall task?
Syntology lines on 5 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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