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ScanNet++

Benchmarks

Task NameDataset NameSOTA ResultTrend
Semantic SegmentationScanNet++ (val)
mIoU52.9
32
Multi-view 3D ReconstructionScanNet++ (test)
AUC@5cm59
30
Camera Pose EstimationScanNet++ DA3
AUC582.66
20
Indoor Semantic SegmentationScanNet++ (val)
mIoU50.7
20
Sparse-view 3D reconstructionScanNet++ (test)
PSNR18.777
18
3D Semantic SegmentationScanNet++ (val)
mAcc55.8
16
3D Line MappingScanNet++ 30 scenes 16
Accuracy Line (ACC-L)0.1337
16
3D line mappingScanNet++ 16 (30 scenes)
Recall@514.31
16
TSDF ReconstructionScanNet++
Accuracy15.67
15
Semantic SegmentationScanNet++
Mean IoU (mIoU)62.4
15
Monocular Depth EstimationScanNet++ Fisheye
delta1 Accuracy96.7
14
Panoptic SegmentationScanNet++
PQ (Panoptic Quality)77.09
14
Multi-view Camera Pose EstimationScanNet++
RPA @ 5°2,270
14
3D instance segmentationScanNet++ V1 (val)
AP5035.8
12
3D reconstructionScanNet++ DA3 (test)
Overall Score38.9
10
Multi-view Depth EstimationScanNet++ DA3 (test)
Abs Rel Error0.035
10
Depth EstimationScanNet++ DA3 benchmark BASE (test)
AbsRel0.044
10
3D reconstructionScanNet++
Overall Score81.3
10
Video depth estimationScanNet++
Absolute Relative Error4.4
10
3D Object DetectionScanNet++
mAP@0.2581.06
10
3D instance segmentationScanNet++ 100 classes (val)
mAP22.9
9
Novel View SynthesisScanNet++ (Extra)
PSNR23.76
8
Image RestorationScanNet++ DA3 v1 (test)
PSNR22.19
8
3D ReconstructionScanNet++
F1 Score41.1
8
3D Gaussian Splatting CompressionScanNet++ 0.2 compression ratio (test)
LPIPS0.1948
8
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