MT-PNet

Reported on 2 benchmarks across 2 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision2 results

Instance SegmentationonSceneNN
mAP@0.5· 2019-04-01
8.5
best: 47.1 (OccuSeg)
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields arXiv:1904.00699
3D Instance SegmentationonSceneNN
mAP@0.5· 2019-04-01
8.5
best: 47.1 (OccuSeg)
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields arXiv:1904.00699