Jul 26, 2022 · To better accommodate 3D detection properties, ProposalContrast optimizes with both inter-cluster and inter-proposal separation, i.e., ...
[PDF] Unsupervised Pre-training for LiDAR-based 3D Object Detection
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To better accommodate 3D detection properties, ProposalContrast optimizes with both inter-cluster and inter-proposal separation, i.e., sharpening the ...
Aug 31, 2022 · This work addresses the unsupervised pre-training of 3D backbones via proposal-wise contrastive learning in the context of autonomous driving.
Oct 23, 2022 · ProposalContrast: Unsupervised Pre-training for LiDAR-Based 3D Object Detection. Conference paper; First Online: 23 October 2022. pp 17–33; Cite ...
A new unsupervised point cloud pre-training framework, called ProposalContrast, that learns robust 3D representations by contrasting region proposals that ...
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Oct 23, 2022 · To better accommodate 3D detection properties, ProposalContrast optimizes with both inter-cluster and inter-proposal separation, i.e., ...
Jul 26, 2022 · Considering region-level representations are more suitable for 3D object detection, we devise a new unsupervised point cloud pre-training ...
Accurate 3D object detection and understanding for self-driving cars heavily re- lies on LiDAR point clouds, necessitating large amounts of labeled data to ...
To better accommodate 3D detection properties, ProposalContrast optimizes with both inter-cluster and inter-proposal separation, i.e., sharpening the ...
... 3D object detection with the hierarchical pre-training scheme. 3. Paper · Code ... ProposalContrast: Unsupervised Pre-training for LiDAR-based 3D Object Detection.