mlsanityData to 7 Oct 2026

FastPoseCNN: Real-Time Monocular Category-Level Pose and Size Estimation Framework

arXiv 2406.11063 ↗First posted 16 Jun 2024cs.CVcited by 0

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Abstract (arXiv)

The primary focus of this paper is the development of a framework for pose and size estimation of unseen objects given a single RGB image - all in real-time. In 2019, the first category-level pose and size estimation framework was proposed alongside two novel datasets called CAMERA and REAL. However, current methodologies are restricted from practical use because of its long inference time (2-4 fps). Their approach's inference had significant delays because they used the computationally expensive MaskedRCNN framework and Umeyama algorithm. To optimize our method and yield real-time results, our framework uses the efficient ResNet-FPN framework alongside decoupling the translation, rotation, and size regression problem by using distinct decoders. Moreover, our methodology performs pose and size estimation in a global context - i.e., estimating the involved parameters of all captured objects in the image all at once. We perform extensive testing to fully compare the performance in terms of precision and speed to demonstrate the capability of our method.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 24 of its 45 references that are in the map. First posted on arXiv 16 Jun 2024.

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References · 24

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  3. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 768
  4. 2019Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimationcited by 490
  5. 2019DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusioncited by 352
  6. 2017SSD-6D: Making RGB-based 3D detection and 6D pose estimation great againcited by 243
  7. 2018Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objectscited by 237
  8. 2017T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objectscited by 210
  9. 2019DPOD: 6D Pose Object Detector and Refinercited by 189
  10. 2019Implicit 3D Orientation Learning for 6D Object Detection from RGB Imagescited by 170
  11. 2018Segmentation-driven 6D Object Pose Estimationcited by 104
  12. 2015Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Viewscited by 94
12 more
  1. 2019LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimationcited by 88
  2. 2018Making Deep Heatmaps Robust to Partial Occlusions for 3D Object Pose Estimationcited by 74
  3. 2014Viewpoints and Keypointscited by 59
  4. 2020G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Featurescited by 35
  5. 20206D Object Pose Regression via Supervised Learning on Point Cloudscited by 33
  6. 2020Robust 6D Object Pose Estimation by Learning RGB-D Featurescited by 25
  7. 2018Category-level 6D Object Pose Recovery in Depth Imagescited by 21
  8. 2018SilhoNet: An RGB Method for 6D Object Pose Estimationcited by 14
  9. 2019MaskedFusion: Mask-based 6D Object Pose Estimationcited by 9
  10. 2019ConvPoseCNN: Dense Convolutional 6D Object Pose Estimationcited by 7
  11. 20176D Object Pose Estimation with Depth Images: A Seamless Approach for Robotic Interaction and Augmented Realitycited by 6
  12. 2019W-PoseNet: Dense Correspondence Regularized Pixel Pair Pose Regressioncited by 6

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