Unsupervised 3D category discovery and point labeling from a large ...
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In this paper, we propose, for the first time, to mine category shape patterns directly from a large urban environment, thus constructing a category structure ...
In this paper, we propose, for the first time, to mine category shape patterns directly from a large urban environment, thus constructing a category structure ...
This paper proposes, for the first time, to mine category shape patterns directly from a large urban environment, thus constructing a category structure ...
Step 1: Generate raw shape patterns. (repetitive pattern discovery). Step 2: Common shape refinement within each pattern. (detailed segmentation). We focus on ...
In this paper, we propose, for the first time, to mine category shape patterns directly from a large urban environment, thus constructing a category structure ...
Given an unlabeled point cloud of a large urban environment and a small number of object seeds in a category, we aim to mine a set of models to provide object- ...
Nov 13, 2024 · We present a method for mobile robots to learn the concept of objects and categorize them without supervision using 3D point clouds from a laser scanner as ...
Missing: large urban environment.
Unsupervised 3D category discovery and point labeling from a large urban environment. Conference Paper. Full-text available. May 2013. Quanshi Zhang ...
Abstract We present a method for mobile robots to learn the concept of objects and categorize them without supervision using 3D point clouds from a laser ...
Missing: urban | Show results with:urban
Jun 26, 2024 · Autonomous driving requires reliable detection of 3D objects (e.g. vehicle and cyclist) in urban scenes for safe path planning and navigation.