3D Semantic Instance Segmentation
6 papers with code • 2 benchmarks • 1 datasets
Image: 3D-SIS
ScanNet
Most implemented papers
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
Experimental results on various 3D scenes show the effectiveness of our method on 3D instance segmentation, and we also evaluate the capability of SGPN to improve 3D object detection and semantic segmentation results.
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans
We introduce 3D-SIS, a novel neural network architecture for 3D semantic instance segmentation in commodity RGB-D scans.
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields
Deep learning techniques have become the to-go models for most vision-related tasks on 2D images.
3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation
We show that grouping proposals improves over NMS and outperforms previous state-of-the-art methods on the tasks of 3D object detection and semantic instance segmentation on the ScanNetV2 benchmark and the S3DIS dataset.
3D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance Segmentation
We show that grouping proposals improves over NMS and outperforms previous state-of-the-art methods on the tasks of 3D object detection and semantic instance segmentation on the ScanNetV2 benchmark and the S3DIS dataset.
Mask3D: Mask Transformer for 3D Semantic Instance Segmentation
Modern 3D semantic instance segmentation approaches predominantly rely on specialized voting mechanisms followed by carefully designed geometric clustering techniques.
