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Every9D-21M dataset released for 9D object pose estimation

By PulseAugur Editorial · [3 sources] ·

Researchers have introduced Every9D-21M, a new dataset designed to address the challenge of estimating the 9D pose of everyday objects from single images. This dataset significantly surpasses previous benchmarks, containing 21.8 million real-world images across 700 object categories, derived from 109,000 object-centric videos. The creation of Every9D-21M involved leveraging multi-view geometry to reconstruct point clouds and aligning instances into a shared canonical coordinate frame, with manual annotations propagated through cross-instance alignment and verified from multiple viewpoints. The dataset aims to serve as a benchmark for 9D pose foundation models and has demonstrated improvements in performance on existing datasets like ImageNet3D and PASCAL3D+. AI

IMPACT Establishes a new, large-scale benchmark for 9D object pose estimation, potentially accelerating research and development in computer vision foundation models.

RANK_REASON The cluster describes a new dataset and associated research paper for computer vision, specifically for 9D object pose estimation.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

Every9D-21M dataset released for 9D object pose estimation

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The cluster describes a new dataset and associated research paper for computer vision, specifically for 9D object pose estimation.
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COVERAGE [3]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Every9D-21M: Large-Scale Real-World 9D Canonicalization of Everyday Objects

    Estimating the 9D pose of everyday objects from a single real-world image remains challenging. This is largely due to the lack of large-scale supervision. Most existing datasets either rely heavily on synthetic renderings or provide limited coverage of real-world objects: the lar…

  2. arXiv cs.CV TIER_1 English(EN) · Leonhard Sommer, Emil Akopyan, Adam Kortylewski ·

    Every9D-21M: Large-Scale Real-World 9D Canonicalization of Everyday Objects

    arXiv:2605.28270v1 Announce Type: new Abstract: Estimating the 9D pose of everyday objects from a single real-world image remains challenging. This is largely due to the lack of large-scale supervision. Most existing datasets either rely heavily on synthetic renderings or provide…

  3. arXiv cs.CV TIER_1 English(EN) · Adam Kortylewski ·

    Every9D-21M: Large-Scale Real-World 9D Canonicalization of Everyday Objects

    Estimating the 9D pose of everyday objects from a single real-world image remains challenging. This is largely due to the lack of large-scale supervision. Most existing datasets either rely heavily on synthetic renderings or provide limited coverage of real-world objects: the lar…

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