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Models/DeepViewAgg

DeepViewAgg

Reported on 17 benchmarks across 3 tasks · 1 paper · 10 SOTA

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

Medical7 results

Semantic SegmentationonS3DIS
Params (M)· 2022-04-15
41.2
best: 41.6 (PointNeXt-XL)
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
Semantic SegmentationonS3DIS
mAcc· 2022-04-15
83.8
best: 89.9 (Sonata + PTv3)
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
Semantic SegmentationonKITTI-360
miou· uses extra data· 2022-04-15
58.3
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
Semantic SegmentationonKITTI-360
miou Val· uses extra data· 2022-04-15
57.8
best: 64.1 (DA-supervised)
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
Semantic SegmentationonS3DIS
Mean IoU· 2022-04-15
74.7
best: 82.3 (Sonata + PTv3)
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
Semantic SegmentationonS3DIS
oAcc· 2022-04-15
90.1
best: 93.3 (Sonata + PTv3)
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
Semantic SegmentationonKITTI-360
mIoU Category· uses extra data· 2022-04-15
73.66
best: 74.08 (MinkowskiNet)
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548

Audio7 results

10-shot image generationonS3DIS
Params (M)· 2022-04-15
41.2
best: 41.6 (PointNeXt-XL)
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
10-shot image generationonS3DIS
mAcc· 2022-04-15
83.8
best: 89.9 (Sonata + PTv3)
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
10-shot image generationonKITTI-360
miou· uses extra data· 2022-04-15
58.3
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
10-shot image generationonKITTI-360
miou Val· uses extra data· 2022-04-15
57.8
best: 64.1 (DA-supervised)
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
10-shot image generationonS3DIS
Mean IoU· 2022-04-15
74.7
best: 82.3 (Sonata + PTv3)
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
10-shot image generationonS3DIS
oAcc· 2022-04-15
90.1
best: 93.3 (Sonata + PTv3)
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
10-shot image generationonKITTI-360
mIoU Category· uses extra data· 2022-04-15
73.66
best: 74.08 (MinkowskiNet)
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548

Computer Vision3 results

3D Semantic SegmentationonKITTI-360
miou· uses extra data· 2022-04-15
58.3
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
3D Semantic SegmentationonKITTI-360
miou Val· uses extra data· 2022-04-15
57.8
best: 64.1 (DA-supervised)
SOTA
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548
3D Semantic SegmentationonKITTI-360
mIoU Category· uses extra data· 2022-04-15
73.66
best: 74.08 (MinkowskiNet)
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation arXiv:2204.07548