FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects
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Cited by 26 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
We present FoundationPose, a unified foundation model for 6D object pose estimation and tracking, supporting both model-based and model-free setups. Our approach can be instantly applied at test-time to a novel object without fine-tuning, as long as its CAD model is given, or a small number of reference images are captured. We bridge the gap between these two setups with a neural implicit representation that allows for effective novel view synthesis, keeping the downstream pose estimation modules invariant under the same unified framework. Strong generalizability is achieved via large-scale synthetic training, aided by a large language model (LLM), a novel transformer-based architecture, and contrastive learning formulation. Extensive evaluation on multiple public datasets involving challenging scenarios and objects indicate our unified approach outperforms existing methods specialized for each task by a large margin. In addition, it even achieves comparable results to instance-level methods despite the reduced assumptions. Project page: https://nvlabs.github.io/FoundationPose/
Key facts. Cited by 415 papers in the map (data through 13 Oct 2026). Builds on 64 of its 79 references that are in the map. First posted on arXiv 13 Dec 2023.
Builds on
64 of 79 references.
References · 64
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- 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 770
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- 2020CosyPose: Consistent multi-view multi-object 6D pose estimationcited by 287
- 2018DeepIM: Deep Iterative Matching for 6D Pose Estimationcited by 283
- 2018BOP: Benchmark for 6D Object Pose Estimationcited by 254
- 2018Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objectscited by 237
- 2019Kornia: an Open Source Differentiable Computer Vision Library for PyTorchcited by 232
- 2019Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimationcited by 218
- 2017T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objectscited by 210
- 2019PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimationcited by 204
- 2022MegaPose: 6D Pose Estimation of Novel Objects via Render & Comparecited by 200
- 2020Shape Prior Deformation for Categorical 6D Object Pose and Size Estimationcited by 159
- 2022OnePose: One-Shot Object Pose Estimation without CAD Modelscited by 156
- 2023BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objectscited by 146
- 2021FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimationcited by 144
- 2020Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimationcited by 123
- 2022Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Imagescited by 120
- 2023OnePose++: Keypoint-Free One-Shot Object Pose Estimation without CAD Modelscited by 114
- 2021SurfEmb: Dense and Continuous Correspondence Distributions for Object Pose Estimation with Learnt Surface Embeddingscited by 95
- 2019PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Trackingcited by 91
- 2020se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domainscited by 89
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50 most cited of 64 All 64 (JSON)
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Citing papers per year: 2023: 1; 2024: 52; 2025: 174; 2026: 188.
415 papers.
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50 most cited of 415 All 415 (JSON)
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