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SotA/Computer Vision/3D Semantic Segmentation

3D Semantic Segmentation

46 benchmarks348 papers

3D Semantic Segmentation is a computer vision task that involves dividing a 3D point cloud or 3D mesh into semantically meaningful parts or regions. The goal of 3D semantic segmentation is to identify and label different objects and parts within a 3D scene, which can be used for applications such as robotics, autonomous driving, and augmented reality.

Benchmarks

3D Semantic Segmentation on ScanNet200

val mIoUtest mIoU

3D Semantic Segmentation on DALES

mIoUOverall AccuracyModel size

3D Semantic Segmentation on ScanNet++

Top-1 IoUTop-3 IoU

3D Semantic Segmentation on SensatUrban

mIoUoAcc

3D Semantic Segmentation on Toronto-3D

OAmIoU

3D Semantic Segmentation on KITTI-360

miou ValmioumIoU CategoryModel size

3D Semantic Segmentation on PartNet

mIOU

3D Semantic Segmentation on STPLS3D

mIOU

3D Semantic Segmentation on S3DIS

mIoU (6-Fold)mIoU (Area-5)mAcc

3D Semantic Segmentation on RELLIS-3D Dataset

Mean IoU (class)

3D Semantic Segmentation on ScribbleKITTI

mIoUmIoU-1%

3D Semantic Segmentation on SemanticKITTI

Speed (FPS)mIoUParameters (M)mIoU-1%test mIoUval mIoU

3D Semantic Segmentation on WildScenes

mIoUmIoU (Temporal DA)mIoU (Env DA)

3D Semantic Segmentation on OpenTrench3D

mIoUmAccModel Size

3D Semantic Segmentation on Hypersim

mIoUmIoU (test)

3D Semantic Segmentation on ScanNetV2

mIoU

3D Semantic Segmentation on Waymo Open Dataset

mIoU

3D Semantic Segmentation on 3D Platelet EM

Mean IoU (test)

3D Semantic Segmentation on ECLAIR

F1Mean IoU

3D Semantic Segmentation on SemanticKITTI-C

mean Corruption Error (mCE)

3D Semantic Segmentation on WOD-C

mean Corruption Error (mCE)

3D Semantic Segmentation on nuScenes

mIoU

3D Semantic Segmentation on nuScenes-C

mean Corruption Error (mCE)