Browse State-of-the-Art › 3D Reconstruction
3D Reconstruction
793 papers with code · 10 benchmarks · 58 datasets archive 2025-07-28
3D Reconstruction is the task of creating a 3D model or representation of an object or scene from 2D images or other data sources. The goal of 3D reconstruction is to create a virtual representation of an object or scene that can be used for a variety of purposes, such as visualization, animation, simulation, and analysis. It can be used in fields such as computer vision, robotics, and virtual reality.
Image: Gwak et al
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
58 datasets whose archive record lists this task, ordered by the archive's paper count. 30 shown of 58 until expanded.
Subtasks archive 2025-07-28
7 subtasks in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 793 papers with code (2,326 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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16 Jan 2022 17 repositories listed Syntology ran 18 of 44 samples · 26 unverified · 9 pointer-only (licence)Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate.
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2 Apr 2016 13 repositories listedInspired by the recent success of methods that employ shape priors to achieve robust 3D reconstructions, we propose a novel recurrent neural network architecture that we call the 3D Recurrent Reconstruction Neural…
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6 Oct 2019 12 repositories listed Syntology ran 0 of 5 samples · 5 unverifiedWe provide an open-source C++ library for real-time metric-semantic visual-inertial Simultaneous Localization And Mapping (SLAM).
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24 Jul 2018 9 repositories listedWe evaluate the model using a calibration dataset with several different lenses and compare the models using the metrics that are relevant for Visual Odometry, i.
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10 Dec 2018 7 repositories listed Syntology ran 13 of 23 samples · 10 unverifiedWith the advent of deep neural networks, learning-based approaches for 3D reconstruction have gained popularity.
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1 Jan 2021 6 repositories listedAs a result, we achieve promising results on all datasets and the highest F-Score on the online TNT intermediate benchmark.
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10 Mar 2020 6 repositories listed Syntology ran 7 of 21 samples · 14 unverifiedRecently, implicit neural representations have gained popularity for learning-based 3D reconstruction.
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21 Aug 2019 5 repositories listedPointNet has recently emerged as a popular representation for unstructured point cloud data, allowing application of deep learning to tasks such as object detection, segmentation and shape completion.
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4 Mar 2019 5 repositories listedWe propose instead to tightly couple mesh regularization and state estimation by detecting and enforcing structural regularities in a novel factor-graph formulation.
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31 Jan 2019 5 repositories listed Syntology ran 1 of 9 samples · 8 unverifiedThen, a context-aware fusion module is introduced to adaptively select high-quality reconstructions for each part (e.
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16 Jan 2019 5 repositories listed Syntology ran 2 of 7 samples · 5 unverified · 1 pointer-only (licence)In this work, we introduce DeepSDF, a learned continuous Signed Distance Function (SDF) representation of a class of shapes that enables high quality shape representation, interpolation and completion from partial and…
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7 Apr 2018 5 repositories listedWe present an end-to-end deep learning architecture for depth map inference from multi-view images.
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24 Feb 2025 4 repositories listed Syntology ran 1 of 6 samples · 5 unverifiedWe find that MegaLoc (1) achieves state of the art on a large number of Visual Place Recognition datasets, (2) impressive results on common Landmark Retrieval datasets, and (3) sets a new state of the art for Visual…
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21 Feb 2023 4 repositories listed Syntology ran 2 of 6 samples · 4 unverifiedWe consider the problem of reconstructing a full 360{\deg} photographic model of an object from a single image of it.
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5 Jan 2021 4 repositories listed Syntology ran 1 of 1 samples · 0 unverifiedEstablishing dense correspondences between a pair of images is an important and general problem.
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30 Jul 2020 4 repositories listedWe present a solution to the problem of visual odometry from the data acquired by a stereo event-based camera rig.
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23 Mar 2020 4 repositories listed Syntology ran 0 of 16 samples · 16 unverifiedThis work focuses on mitigating two limitations in the joint learning of local feature detectors and descriptors.
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13 Dec 2019 4 repositories listed Syntology ran 6 of 14 samples · 8 unverifiedThe deep multi-view stereo (MVS) and stereo matching approaches generally construct 3D cost volumes to regularize and regress the output depth or disparity.
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9 May 2019 4 repositories listed Syntology ran 1 of 13 samples · 12 unverified · 1 pointer-only (licence)In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions.
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6 Dec 2018 4 repositories listedWe advocate the use of implicit fields for learning generative models of shapes and introduce an implicit field decoder, called IM-NET, for shape generation, aimed at improving the visual quality of the generated shapes.
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19 Jul 2018 4 repositories listedEvent cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision.
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31 May 2017 4 repositories listedFor the past decade, convolutional networks have been used for 3D reconstruction of neurons from electron microscopic (EM) brain images.
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2 Dec 2016 4 repositories listed Syntology ran 2 of 6 samples · 4 unverified · 2 pointer-only (licence)Our final solution is a conditional shape sampler, capable of predicting multiple plausible 3D point clouds from an input image.
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28 Nov 2024 3 repositories listed Syntology ran 2 of 17 samples · 15 unverifiedWe present DiffVox, a self-supervised framework for Cone-Beam Computed Tomography (CBCT) reconstruction by directly optimizing a voxelgrid representation using physics-based differentiable X-ray rendering.
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8 Apr 2023 3 repositories listedHowever, PX only provides a flattened 2D image, lacking in a 3D view of the oral structure.
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18 Oct 2022 3 repositories listedThis approach of image scraping and selection relaxes the need for a real-world domain-specific dataset that must be either publicly available or created for this purpose.
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30 Jun 2022 3 repositories listedReconstruction of the soft tissues in robotic surgery from endoscopic stereo videos is important for many applications such as intra-operative navigation and image-guided robotic surgery automation.
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27 Apr 2022 3 repositories listedWe demonstrate that employing the proposed Power Bundle Adjustment as a sub-problem solver significantly improves speed and accuracy of the distributed optimization.
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3 Mar 2022 3 repositories listed Syntology ran 0 of 6 samples · 6 unverifiedThis paper studies the complex task of simultaneous multi-object 3D reconstruction, 6D pose and size estimation from a single-view RGB-D observation.
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18 Aug 2021 3 repositories listed Syntology ran 0 of 10 samples · 10 unverifiedFinding local features that are repeatable across multiple views is a cornerstone of sparse 3D reconstruction.
Syntology lines on 16 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