Jenga Stacking Based on 6D Pose Estimation for Architectural Form Finding Process
Not on the map. Why?
Abstract (arXiv)
This paper includes a review of current state of the art 6d pose estimation methods, as well as a discussion of which pose estimation method should be used in two types of architectural design scenarios. Taking the latest pose estimation research Gen6d as an example, we make a qualitative assessment of the current openset methods in terms of application level, prediction speed, resistance to occlusion, accuracy, resistance to environmental interference, etc. In addition, we try to combine 6D pose estimation and building wind environment assessment to create tangible architectural design approach, we discuss the limitations of the method and point out the direction in which 6d pose estimation is eager to progress in this scenario.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 13 of its 27 references that are in the map. First posted on arXiv 18 Nov 2023.
Builds on
13 of 27 references.
References · 13
- 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
- 2018PVNet: Pixel-wise Voting Network for 6DoF Pose Estimationcited by 385
- 2017BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depthcited by 225
- 2017Real-Time Seamless Single Shot 6D Object Pose Predictioncited by 210
- 2019Implicit 3D Orientation Learning for 6D Object Detection from RGB Imagescited by 170
- 2022Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Imagescited by 121
- 2019Single-Stage 6D Object Pose Estimationcited by 88
- 2022FS6D: Few-Shot 6D Pose Estimation of Novel Objectscited by 81
- 2022CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimationcited by 70
- 2015Learning Descriptors for Object Recognition and 3D Pose Estimationcited by 60
- 2019Multi-path Learning for Object Pose Estimation Across Domainscited by 52
- 2018Occlusion Resistant Object Rotation Regression from Point Cloud Segmentscited by 9
Built on by
Not cited yet.