We propose a contrastive learning approach which encodes each single frame of the collected raw data into a feature vector that can be effectively classified.

We propose a contrastive learning approach which encodes each single frame of the collected raw data into a feature vector that can be effectively classified.

A self-supervised method and a corresponding package to classify driving scenes in large-scale point cloud data using a contrastive learning approach which ...

We propose an adaptive approach to 3-D object classification. In this approach appropriate 3-D feature descriptor algorithms for 3-D point clouds are selected ...

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PSCO: A POINT CLOUD SCENE CLASSIFICATION MODEL BASED ON CONTRAST LEARNING ; Session: MA.L410: Autonomous Vehicle Vision Lecture ; Track: Special Sessions ...

PSCO: A POINT CLOUD SCENE CLASSIFICATION MODEL BASED ON CONTRAST LEARNING. SPS. Members: Free IEEE Members: $11.00. Non-members: $15.00.

PSCO: A POINT CLOUD SCENE CLASSIFICATION MODEL BASED ON CONTRAST LEARNING. 09 Oct 2023. PSCO: A POINT CLOUD SCENE CLASSIFICATION MODEL BASED ON CONTRAST ...

Publications (7) · Rethinking Masked-Autoencoder-Based 3D Point Cloud Pretraining · PSCO: A Point Cloud Scene Classification Model Based on Contrast Learning.

Nov 28, 2023 · In this study, we propose a new algorithm called Diffusion Unit (DU) that handles edge information in a principled and interpretable manner while providing ...