mlsanityData to 7 Oct 2026

DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation

arXiv 2107.12549 ↗First posted 27 Jul 2021cs.CVcited by 12

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Abstract (arXiv)

Scalable 6D pose estimation for rigid objects from RGB images aims at handling multiple objects and generalizing to novel objects. Building on a well-known auto-encoding framework to cope with object symmetry and the lack of labeled training data, we achieve scalability by disentangling the latent representation of auto-encoder into shape and pose sub-spaces. The latent shape space models the similarity of different objects through contrastive metric learning, and the latent pose code is compared with canonical rotations for rotation retrieval. Because different object symmetries induce inconsistent latent pose spaces, we re-entangle the shape representation with canonical rotations to generate shape-dependent pose codebooks for rotation retrieval. We show state-of-the-art performance on two benchmarks containing textureless CAD objects without category and daily objects with categories respectively, and further demonstrate improved scalability by extending to a more challenging setting of daily objects across categories.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 46 of its 65 references that are in the map. First posted on arXiv 27 Jul 2021.

Builds on

46 of 65 references.

References · 46

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34 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 5; 2024: 3; 2025: 1; 2026: 2.

12 papers.

  1. 2022Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Imagescited by 120
  2. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 39
  3. 2023Challenges for Monocular 6D Object Pose Estimation in Roboticscited by 21
  4. 2023SOCS: Semantically-aware Object Coordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variationscited by 12
  5. 2023GS-Pose: Category-Level Object Pose Estimation via Geometric and Semantic Correspondencecited by 12
  6. 2024Extreme Two-View Geometry From Object Poses with Diffusion Modelscited by 4
  7. 2023RGB-D-Based Categorical Object Pose and Shape Estimation: Methods, Datasets, and Evaluationcited by 2
  8. 2023Open Challenges for Monocular Single-shot 6D Object Pose Estimationcited by 2
  9. 2024Generalizable Single-view Object Pose Estimation by Two-side Generating and Matchingcited by 1
  10. 2025Category-Level 6D Object Pose Estimation in Agricultural Settings Using a Lattice-Deformation Framework and Diffusion-Augmented Synthetic Datacited by 1
  11. 2026Mind the Shape Gap: A Benchmark and Baseline for Deformation-Aware 6D Pose Estimation of Agricultural Producecited by 1
  12. 2026Learning Positive-Incentive Point Sampling in Neural Implicit Fields for Object Pose Estimationcited by 0