Dec 20, 2022 · Our main idea is to learn more discriminative features from different geometric descriptors by sparse convolution and attention mechanism.
ABSTRACT. Part segmentation is one of the important tasks in 3D shape anal- ysis. Prior works mostly rely on complex local modeling to learn.
This paper describes a non-contact optical measuring approach by which to measure the three-dimensional (3D) shape of a transparent object such as a glass ...
A light and efficient attention model for 3D shape part-segmentation. https ... VoxSegNet: Volumetric CNNs for Semantic Part Segmentation of 3D Shapes.
We proposed a simple, fast and robust approach for 3D shape part segmentation without sophisticated local geometric modeling and ingenious networks. Our main ...
A light and efficient attention model for 3D shape part-segmentation. W. Shi, and Z. Li. CSSE, page 287-292. ACM, (2022 ). Links and resources. BibTeX key ...
Publication Results. A light and efficient attention model for 3D shape part-segmentation. Publication type: Conference Proceeding.
[PDF] 3D Shape Part Segmentation by Vision-Language Model Distillation
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This paper proposes a cross-modal distillation frame- work, PartDistill, which transfers 2D knowledge from vision-language models (VLMs) to facilitate 3D ...
Missing: light | Show results with:light
We propose a fast method for 3D shape segmentation and labeling via Extreme Learning Machine (ELM). Given a set of example shapes with labeled segmentation, ...
In this paper, we address the problem of segmentation and labelling of the 3D point clouds by proposing a inception based deep network architecture called PIG- ...