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SfM-TTR: Using Structure from Motion for Test-Time Refinement of Single-View Depth Networks
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Estimating a dense depth map from a single view is geometrically ill-posed, and state-of-the-art methods rely on learning depth's relation with visual appearance using deep neural networks. On the other hand, Structure from Motion (SfM) leverages multi-view constraints to produce very accurate but sparse maps, as matching across images is typically ...
Sergio Izquierdo, Javier Civera 0001
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MP-SfM: Monocular Surface Priors for Robust Structure-From-Motion
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)While Structure-from-Motion (SfM) has seen much progress over the years, state-of-the-art systems are prone to failure when facing extreme viewpoint changes in low-overlap, low-parallax or high-symmetry scenarios. Because capturing images that avoid these pitfalls is challenging, this severely limits the wider use of SfM, especially by non-expert users.
Zador Pataki +3 more
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Archival photogrammetric analysis of river–floodplain systems using Structure from Motion (SfM) methods [PDF]
Earth Surface Processes and Landforms, 2016 AbstractIn this study we evaluate the extent to which accurate topographic data can be obtained by applying Structure from Motion (SfM) photogrammetric methods to archival imagery. While SfM has proven valuable in photogrammetric applications using specially acquired imagery (e.g. from unmanned aerial vehicles), it also has the potential to improve the
Bakker Maarteen, Lane Stuart N.
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ACCURACY OF 3D RECONSTRUCTION IN AN ILLUMINATION DOME [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 The accuracy of 3D surface reconstruction was compared from image sets of a Metric Test Object taken in an illumination dome by two methods: photometric stereo and improved structure-from-motion (SfM), using point cloud data from a 3D colour laser ...
L. MacDonald +5 more
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Incremental Structure from Motion for Small-Scale Scenes Based on Auxiliary Calibration
SensorsScarce feature points are a critical limitation affecting the accuracy and stability of incremental structure from motion (SfM) in small-scale scenes. In this paper, we propose an incremental SfM method for small-scale scenes, combined with an auxiliary ...
Sixu Li +4 more
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Short communication: Challenges and applications of structure-from-motion photogrammetry in a physical model of a braided river [PDF]
Earth Surface Dynamics, 2019 For extending the applications of structure-from-motion (SfM) photogrammetry in river flumes, we present the main challenges and methods used to collect a large dataset (>1000 digital elevation models, DEMs) of high-quality topographic data using ...
P. Leduc, S. Peirce, P. Ashmore
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Machine Learning Vegetation Filtering of Coastal Cliff and Bluff Point Clouds
Remote SensingCoastal cliffs erode in response to short- and long-term environmental changes, but predicting these changes continues to be a challenge. In addition to a chronic lack of data on the cliff face, vegetation presence and growth can bias our erosion ...
Phillipe Alan Wernette
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Science & Justice, 2021 The recovery of three-dimensional footwear impressions at crime scenes can be a challenge but can also yield important investigative data. Traditional methods involve casting 3D impressions but these methods have limitations: the trace is usually destroyed during capture; the process can be time consuming, with a risk of failure; and the resultant cast
Hannah Larsen +2 more
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Divergent mechanisms of perceptual reversals in spinning and wobbling structure-from-motion stimuli.
PLoS ONEThis study explores the visual phenomenon of random dot structure-from-motion (SFM), where the brain perceives 3D shapes from the coordinated 2D motion of dots.
Leo Poom
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