task_path stringlengths 3 199 ⌀ | dataset stringlengths 1 128 ⌀ | model_name stringlengths 1 223 ⌀ | paper_url stringlengths 21 601 ⌀ | metric_name stringlengths 1 50 ⌀ | metric_value stringlengths 1 9.22k ⌀ |
|---|---|---|---|---|---|
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | ScanNet200 | LGround | https://arxiv.org/abs/2204.07761v2 | val mIoU | 28.8 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | ScanNet200 | LGround | https://arxiv.org/abs/2204.07761v2 | test mIoU | 27.2 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | ScanNet200 | CSC | https://arxiv.org/abs/2012.09165v3 | val mIoU | 26.4 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | ScanNet200 | CSC | https://arxiv.org/abs/2012.09165v3 | test mIoU | 24.9 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | ScanNet200 | MinkUNet | https://arxiv.org/abs/1904.08755v4 | val mIoU | 25.0 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | ScanNet200 | MinkUNet | https://arxiv.org/abs/1904.08755v4 | test mIoU | 25.3 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | SCF-Net | http://openaccess.thecvf.com//content/CVPR2021/html/Fan_SCF-Net_Learning_Spatial_Contextual_Features_for_Large-Scale_Point_Cloud_Segmentation_CVPR_2021_paper.html | OA | 95.50 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | SCF-Net | http://openaccess.thecvf.com//content/CVPR2021/html/Fan_SCF-Net_Learning_Spatial_Contextual_Features_for_Large-Scale_Point_Cloud_Segmentation_CVPR_2021_paper.html | mIoU | 73.60 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | RandLANet | https://arxiv.org/abs/1911.11236v3 | OA | 93.50 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | RandLANet | https://arxiv.org/abs/1911.11236v3 | mIoU | 68.40 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | KPFCNN | https://arxiv.org/abs/2003.08284v3 | OA | 91.71 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | KPFCNN | https://arxiv.org/abs/2003.08284v3 | mIoU | 60.30 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | TGNet | https://arxiv.org/abs/2003.08284v3 | OA | 91.64 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | TGNet | https://arxiv.org/abs/2003.08284v3 | mIoU | 58.34 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | MS-PCNN | https://arxiv.org/abs/2003.08284v3 | OA | 91.53 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | MS-PCNN | https://arxiv.org/abs/2003.08284v3 | mIoU | 58.01 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | PointNet++ | https://arxiv.org/abs/2003.08284v3 | OA | 91.21 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | PointNet++ | https://arxiv.org/abs/2003.08284v3 | mIoU | 56.55 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | DGCNN | https://arxiv.org/abs/2003.08284v3 | OA | 89.00 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | Toronto-3D | DGCNN | https://arxiv.org/abs/2003.08284v3 | mIoU | 49.60 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | KPConv | https://arxiv.org/abs/1904.08889v2 | mIoU | 81.1 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | KPConv | https://arxiv.org/abs/1904.08889v2 | Overall Accuracy | 97.8 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | KPConv | https://arxiv.org/abs/1904.08889v2 | Model size | 14M |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | Superpoint Transformer | https://arxiv.org/abs/2306.08045v2 | mIoU | 79.6 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | Superpoint Transformer | https://arxiv.org/abs/2306.08045v2 | Overall Accuracy | 97.5 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | Superpoint Transformer | https://arxiv.org/abs/2306.08045v2 | Model size | 212K |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | EyeNet | https://arxiv.org/abs/2301.12972v3 | mIoU | 79.6 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | SuperCluster | https://arxiv.org/abs/2401.06704v2 | mIoU | 77.3 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | SuperCluster | https://arxiv.org/abs/2401.06704v2 | Model size | 210M |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | PointNet++ | http://arxiv.org/abs/1706.02413v1 | mIoU | 68.3 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | PointNet++ | http://arxiv.org/abs/1706.02413v1 | Overall Accuracy | 95.7 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | PointNet++ | http://arxiv.org/abs/1706.02413v1 | Model size | 3.0M |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | ConvPoint | https://arxiv.org/abs/1904.02375v5 | mIoU | 67.4 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | ConvPoint | https://arxiv.org/abs/1904.02375v5 | Overall Accuracy | 97.2 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | ConvPoint | https://arxiv.org/abs/1904.02375v5 | Model size | 4.7M |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | SPG | http://arxiv.org/abs/1711.09869v2 | mIoU | 60.6 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | SPG | http://arxiv.org/abs/1711.09869v2 | Overall Accuracy | 95.5 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | SPG | http://arxiv.org/abs/1711.09869v2 | Model size | 280K |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | PointCNN | http://papers.nips.cc/paper/7362-pointcnn-convolution-on-x-transformed-points | mIoU | 58.4 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | PointCNN | http://papers.nips.cc/paper/7362-pointcnn-convolution-on-x-transformed-points | Overall Accuracy | 97.2 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | PointCNN | http://papers.nips.cc/paper/7362-pointcnn-convolution-on-x-transformed-points | Model size | null |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | ShellNet | https://arxiv.org/abs/1908.06295v1 | mIoU | 57.4 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | ShellNet | https://arxiv.org/abs/1908.06295v1 | Overall Accuracy | 96.4 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | DALES | ShellNet | https://arxiv.org/abs/1908.06295v1 | Model size | null |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | STPLS3D | KpConv | https://arxiv.org/abs/1904.08889v2 | mIOU | 53.73 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | STPLS3D | PointCT | https://openaccess.thecvf.com/content/WACV2024/html/Tran_PointCT_Point_Central_Transformer_Network_for_Weakly-Supervised_Point_Cloud_Semantic_WACV_2024_paper.html | mIOU | 53.2 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | STPLS3D | MinkowskiNet | https://arxiv.org/abs/1904.08755v4 | mIOU | 51.3 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | STPLS3D | SCF-Net | http://openaccess.thecvf.com//content/CVPR2021/html/Fan_SCF-Net_Learning_Spatial_Contextual_Features_for_Large-Scale_Point_Cloud_Segmentation_CVPR_2021_paper.html | mIOU | 50.65 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | STPLS3D | Point transformer | https://arxiv.org/abs/2012.09164v2 | mIOU | 47.64 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | STPLS3D | PointNet++ | http://arxiv.org/abs/1706.02413v1 | mIOU | 15.92 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointVector-XL | https://arxiv.org/abs/2205.10528v3 | mIoU | 76.5 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointVector-XL | https://arxiv.org/abs/2205.10528v3 | mAcc | 84.1 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointVector-XL | https://arxiv.org/abs/2205.10528v3 | Model Size | 24.1M |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointMetaBase-XXL | https://arxiv.org/abs/2211.14462v2 | mIoU | 75.8 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointMetaBase-XXL | https://arxiv.org/abs/2211.14462v2 | mAcc | 84.5 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointMetaBase-XXL | https://arxiv.org/abs/2211.14462v2 | Model Size | 19.7M |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointNeXt-XL | https://arxiv.org/abs/2206.04670v2 | mIoU | 70.6 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointNeXt-XL | https://arxiv.org/abs/2206.04670v2 | mAcc | 79.7 |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | OpenTrench3D | PointNeXt-XL | https://arxiv.org/abs/2206.04670v2 | Model Size | 41.5M |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | LSK3DNet | https://arxiv.org/abs/2403.15173v1 | test mIoU | 75.6% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | LSK3DNet | https://arxiv.org/abs/2403.15173v1 | val mIoU | 70.2% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | PPT+PTv3 | https://arxiv.org/abs/2312.10035v2 | test mIoU | 75.5% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | PPT+PTv3 | https://arxiv.org/abs/2312.10035v2 | val mIoU | 72.3% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | UniSeg | https://arxiv.org/abs/2309.05573v1 | test mIoU | 75.2% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | UniSeg | https://arxiv.org/abs/2309.05573v1 | val mIoU | 71.3% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | SphereFormer | https://arxiv.org/abs/2303.12766v1 | test mIoU | 74.8% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | SphereFormer | https://arxiv.org/abs/2303.12766v1 | val mIoU | 67.8% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | DITR | https://arxiv.org/abs/2503.18944v1 | test mIoU | 74.4% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | DITR | https://arxiv.org/abs/2503.18944v1 | val mIoU | 69.0% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | FRNet | https://arxiv.org/abs/2312.04484v3 | test mIoU | 73.3% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | FRNet | https://arxiv.org/abs/2312.04484v3 | val mIoU | 68.7% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | RangeFormer | https://arxiv.org/abs/2303.05367v3 | test mIoU | 73.3% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | RangeFormer | https://arxiv.org/abs/2303.05367v3 | val mIoU | 67.6% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | 2DPASS | https://arxiv.org/abs/2207.04397v3 | test mIoU | 72.9% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | 2DPASS | https://arxiv.org/abs/2207.04397v3 | val mIoU | 69.3% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | PTv2 | https://arxiv.org/abs/2210.05666v2 | test mIoU | 72.6% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | PTv2 | https://arxiv.org/abs/2210.05666v2 | val mIoU | 70.3% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | PVKD | https://arxiv.org/abs/2206.02099v1 | test mIoU | 71.2% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | AF2S3Net | https://arxiv.org/abs/2102.04530v1 | test mIoU | 70.8% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | AF2S3Net | https://arxiv.org/abs/2102.04530v1 | val mIoU | 74.2% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | WaffleIron | https://arxiv.org/abs/2301.10100v2 | test mIoU | 70.8% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | WaffleIron | https://arxiv.org/abs/2301.10100v2 | val mIoU | 68.0% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | Cylinder3D | https://arxiv.org/abs/2011.10033v1 | test mIoU | 68.9% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | Cylinder3D | https://arxiv.org/abs/2011.10033v1 | val mIoU | 64.3% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | SPVNAS | https://arxiv.org/abs/2007.16100v2 | test mIoU | 66.4% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | SPVNAS | https://arxiv.org/abs/2007.16100v2 | val mIoU | 64.7% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | JS3C-Net | https://arxiv.org/abs/2012.03762v1 | test mIoU | 66.0% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | GFNet | https://arxiv.org/abs/2207.02605v2 | test mIoU | 65.4% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | KPRNet | https://arxiv.org/abs/2007.12668v2 | test mIoU | 63.1% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | TORNADONet-HiRes | https://arxiv.org/abs/2008.10544v1 | test mIoU | 63.1% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | NAPL | https://arxiv.org/abs/2210.09948v1 | test mIoU | 61.6% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | Meta-RangeSeg | https://arxiv.org/abs/2202.13377v3 | test mIoU | 61.0% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | BAAF-Net | https://arxiv.org/abs/2103.07074v2 | test mIoU | 59.9% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | SalsaNext | https://arxiv.org/abs/2003.03653v4 | test mIoU | 59.5% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | KPConv | https://arxiv.org/abs/1904.08889v2 | test mIoU | 58.8% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | PolarNet | https://arxiv.org/abs/2003.14032v2 | test mIoU | 57.2% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | FPS-Net | https://arxiv.org/abs/2103.00738v1 | test mIoU | 57.1% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | SqueezeSegV3 | https://arxiv.org/abs/2004.01803v2 | test mIoU | 55.9% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | 3D-MiniNet | https://arxiv.org/abs/2002.10893v5 | test mIoU | 55.8% |
10-shot image generation > Semantic Segmentation > 3D Semantic Segmentation | SemanticKITTI | MPF | https://arxiv.org/abs/2011.01974v2 | test mIoU | 55.5% |
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