CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving. (arXiv:2206.04028v1 [cs.CV])

Unsupervised contrastive learning for indoor-scene point clouds has achieved
great successes. However, unsupervised learning point clouds in outdoor scenes
remains challenging because previous methods need to reconstruct the whole
scene and capture partial views for the contrastive objective. This is
infeasible in outdoor scenes with moving objects, obstacles, and sensors. In
this paper, we propose CO^3, namely Cooperative Contrastive Learning and
Contextual Shape Prediction, to learn 3D representation for outdoor-scene point
clouds in an unsupervised manner. CO^3 has several merits …

3d arxiv autonomous autonomous driving cv driving learning representation representation learning unsupervised