SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud
Open paper
Benchmark
Model
Rank
Results
robust-3d-semantic-segmentation-on-robo3d
SqueezeSegV2 (64x2048)
#20
mean Corruption Error (mCE): 152.45%
3d-semantic-segmentation-on-semantickitti
SqueezeSegV2
#32
test mIoU: 39.7%
Rank counts only results with a code link.