PointBERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling

3D Point Cloud Segmentation with SuperPoint Transformers (and Python)

Talk | CVPR'24 Oral：超越3D - Point Transformer V3中的多模态特征提取新构想

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PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

Recent Advances in Deep Learning for 3D Point Clouds Analysis (Loic Landrieu, IGN)

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Masked Autoencoder for Self-Supervised Pre-training on Lidar Point Clouds [WACV 2023 PLV workshop]

Vision Transformer for Image Classification

[SGP-2022] Deep Learning on Point Clouds

Lecture 05: Point Cloud Encoders (KAIST CS479, Fall 2023)

[Paper Review] Energy-efficient Distributed Heterogeneous Hybrid Flow-shop Scheduling

Neighborhood Attention Transformer (CVPR 2023)

The AI Factory: Infrastructure for Intelligence | Jensen Huang, CEO, NVIDIA

LiDAR Point Cloud Vectorization: 3D Python Tutorial (+ LoD City Models)

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

3D Point Cloud Subsampling: Random, Spatial, and Octree Methods

PoinTr ICCV Presentation

【機器學習2021】自督導式學習 (Self-supervised Learning) (二) – BERT簡介

Transformers Explained | Simple Explanation of Transformers