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Codesota · Tasks · Image-to-3DHome/Tasks/Computer Vision/Image-to-3D
Computer Vision· image-to-3d

Image-to-3D.

Image-to-3D reconstruction infers full 3D geometry from one or a few images — a fundamentally ill-posed problem that recent models solve with learned geometric priors. Traditional multi-view stereo required dozens of calibrated views, but single-image methods like One-2-3-45 (2023) and TripoSR leverage large-scale 3D training data to hallucinate plausible geometry from a single photo. 3D Gaussian Splatting (2023) revolutionized the representation side, enabling real-time rendering of reconstructed scenes. The practical gap is clear: scanned objects still look better than generated ones, but the convenience of snap-and-reconstruct is reshaping e-commerce product visualization and AR content creation.

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Datasets
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Results
composite
Canonical metric
§ 02 · Canonical benchmark

The reference dataset.

GSO (Google Scanned Objects)

Single-image 3D reconstruction evaluated on scanned household objects

Primary metric: composite
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§ 03 · Top 10

Leading models.

Leading models on GSO (Google Scanned Objects).

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§ 04 · All datasets

Tracked datasets.

1 dataset tracked for this task.

GSO (Google Scanned Objects)
CANONICAL
0 results · composite
§ 05 · Related tasks

Other tasks in Computer Vision.

Document Image ClassificationDocument Layout AnalysisDocument ParsingDocument UnderstandingGeneral OCR CapabilitiesHandwriting RecognitionImage Feature ExtractionImage-to-Image
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