Point Transformer

🤖 Plain-English Summary

Self-attention networks have revolutionized natural language processing and are making impressive strides in image analysis tasks such as image classification and object detection. Our Point Transformer design improves upon prior work across domains and tasks.

🔑 Key Findings

• Inspired by this success, we investigate the application of self-attention networks to 3D point cloud processing.
• We design self-attention layers for point clouds and use these to construct self-attention networks for tasks such as semantic scene segmentation, object part segmentation, and object classification.
• Our Point Transformer design improves upon prior work across domains and tasks.

🔗 Related Resources