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Research map / 3D vision / Depth and stereo

Camera model and calibration for SfM

Handles camera calibration, distortion and minimal geometric solvers in large-scale structure from motion.

99 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026) · an approach in Depth and stereo, keyword cluster “motion · flow · localization”

State History Tried Checklist Preprints Who Export

Where it stands

Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.

19 papers in 2023–24 and 17 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 6.2% to 4.2%.

How this is decided

A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.

How it got here

2016: 12162017: 11172018: 11182019: 6192020: 10202021: 5212022: 8222023: 8232024: 11242025: 11252026: 626

Most cited paper of each year

Earliest papers here

What has been tried

91 papers here report 719 measured changes (a component added, removed or swapped, compared with a baseline): helped 68%, no clear effect 7%, hurt 18%, mixed 7%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changedMeasured onResultEffectPaper
use quantization ratio r = 4 instead of r = 8ETH3D · Accuracy (1cm)80.24 -> 81.58HelpedDetector-Free Structure from Motion (CVPR 2024 · 59 citations)
Add feature diffusion rather than identity global encodingCambridge Landmarks · position error (cm)0.8 -> 0.3HelpedGLACE: Global Local Accelerated Coordinate Encoding (CVPR 2024 · 36 citations)
Add overlap supervision during trainingMap-free test · AUC0.74 -> 0.75No clear effectMatching 2D Images in 3D: Metric Relative Pose from Metric Correspondences (CVPR 2024 · 26 citations)
add token-level CamRay to PRoPERealEstate10K with varying intrinsics · PSNR21.42 -> 21.78HelpedCameras as Relative Positional Encoding (NeurIPS 2025 · 10 citations)
Use LocoNet pre-trainingCSRD-II camera registration · Cam.Pos.Avg (m)6.98 -> 0.89HelpedFrom a Bird's Eye View to See: Joint Camera and Subject Registration without the Camera Calibration (CVPR 2024 · 10 citations)
add ADPs to the five VPsSL-MH test · pan error19.38 -> 2.20HelpedDeep Single Image Camera Calibration by Heatmap Regression to Recover Fisheye Images Under Manhattan World Assumption (CVPR 2024 · 5 citations)
add bundle adjustment on K to COLMAPguessFountain-P11 · Re0.444 -> 0.212HelpedMinimal Perspective Autocalibration (CVPR 2024 · 5 citations)
add intrinsic low-DOF motion representationReplica tracking average · ATE-RMSE (cm)0.54 -> 0.49HelpedContinuous Pose for Monocular Cameras in Neural Implicit Representation (CVPR 2024 · 4 citations)
Increase minimum edge score from 0.6 to 0.7Alamo · reconstruction time28 -> 25HelpedLeveraging Camera Triplets for Efficient and Accurate Structure-from-Motion (CVPR 2024 · 4 citations)
Vary the number of calibration control pointsBabelCalib · projection errorMixedStructure-from-Motion with a Non-Parametric Camera Model (CVPR 2025 · 3 citations)
Use hybrid inputs and explicit 3D points instead of relative translations onlyKITTI-00 · median camera position error (m)5.0 -> 3.0HelpedRevisiting Global Translation Estimation with Feature Tracks (CVPR 2024 · 3 citations)
add the unprojection loss LuMipNeRF-360, LLFF, Tanks & Temples, and Aria Everyday Activities · LPIPS0.035 -> 0.021; 0.080 -> 0.069; 0.059 -> 0.056; 0.087 -> 0.076HelpedAnyMap: Learning a General Camera Model for Structure-from-Motion with Unknown Distortion in Dynamic Scenes (CVPR 2025 · 2 citations)

What reviewers will expect

Datasets and baselines named in the 12 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Datasets

  • DAVIS · 2 of 12 papers

Baselines

  • COLMAP · 2 of 12 papers
  • GLOMAP · 2 of 12 papers
  • GeoCalib · 2 of 12 papers
  • MASt3R · 2 of 12 papers
  • CasualSAM · 2 of 12 papers
  • LoFTR · 2 of 12 papers
  • Dust3R · 2 of 12 papers

Recent preprints

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    Who publishes on it

    Institutions on the most papers of this approach since 2023 (of 36 papers; from OpenAlex and the papers' affiliations).

    Use it

    Download BibTeX of 39 key papersOpen the topic in the interactive map

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    Same keyword cluster

    Elsewhere in the topic

    Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).

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