Learned Suppression for 3D Keypoint Detection with a Graph-Transformer Backbone

Name: Learned Suppression for 3D Keypoint Detection with a Graph-Transformer Backbone
Uploaded: 2026-10-03T00:05:19.796570+00:00
Duration: 671 s
Description: The paper introduces a method to detect 3D keypoints using a Graph-Transformer backbone. It addresses challenges in 3D scene understanding by combining graph neural networks with transformer architectures to improve detection accuracy. The approach uses learned suppression techniques to refine point predictions, leading to more precise and robust keypoint localization.

The paper introduces a method to detect 3D keypoints using a Graph-Transformer backbone. It addresses challenges in 3D scene understanding by combining graph neural networks with transformer architectures to improve detection accuracy. The approach uses learned suppression techniques to refine point predictions, leading to more precise and robust keypoint localization.

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