mlsanityData to 14 Oct 2026

GECO: Geometrically Consistent Embedding with Lightspeed Inference

arXiv 2508.00746 ↗First posted 1 Aug 2025cs.CVcited by 6

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Abstract (arXiv)

Recent advances in feature learning have shown that self-supervised vision foundation models can capture semantic correspondences but often lack awareness of underlying 3D geometry. GECO addresses this gap by producing geometrically coherent features that semantically distinguish parts based on geometry (e.g., left/right eyes, front/back legs). We propose a training framework based on optimal transport, enabling supervision beyond keypoints, even under occlusions and disocclusions. With a lightweight architecture, GECO runs at 30 fps, 98.2% faster than prior methods, while achieving state-of-the-art performance on PFPascal, APK, and CUB, improving PCK by 6.0%, 6.2%, and 4.1%, respectively. Finally, we show that PCK alone is insufficient to capture geometric quality and introduce new metrics and insights for more geometry-aware feature learning. Link to project page: https://reginehartwig.github.io/publications/geco/

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 54 of its 69 references that are in the map. First posted on arXiv 1 Aug 2025.

Builds on

54 of 69 references.

References · 54

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38 more
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50 most cited of 54 All 54 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026MARCO: Navigating the Unseen Space of Semantic Correspondencecited by 3
  2. 2026Shape-of-You: Fused Gromov-Wasserstein Optimal Transport for Semantic Correspondence in-the-Wildcited by 1
  3. 2026Geometry Matters: 3D Foundation Priors for Learning Semantic Correspondencecited by 1
  4. 2026Quantum-Inspired Harmonic Decision Models: A Computational Framework for Music Generationcited by 1
  5. 2026Ordered Diffusion for 3D Human Registrationcited by 1
  6. 2026ImCorr: Sub-pixel Semantic Correspondence via Implicit Feature Decodingcited by 0