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 > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | SemiVL (ViT-B/16) | https://arxiv.org/abs/2311.16241v1 | Validation mIoU | 79.4% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | PrevMatch (ResNet-101) | https://arxiv.org/abs/2405.20610v1 | Validation mIoU | 78.9% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | CorrMatch (Deeplabv3+ with ResNet-101) | https://arxiv.org/abs/2306.04300v3 | Validation mIoU | 78.5% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | FARCLUSS | https://arxiv.org/abs/2506.11142v2 | Validation mIoU | 78.5 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | Dual Teacher | https://openreview.net/forum?id=JXvszuOqY3 | Validation mIoU | 78.4 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | UniMatch (DeepLab v3+ with ImageNet-pretrained ResNet-101, single scale inference) | https://arxiv.org/abs/2208.09910v2 | Validation mIoU | 77.92% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | AEL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K) | https://arxiv.org/abs/2110.05474v1 | Validation mIoU | 77.9% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | PrevMatch (ResNet-50) | https://arxiv.org/abs/2405.20610v1 | Validation mIoU | 77.8% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | S4MC | https://arxiv.org/abs/2308.13900v2 | Validation mIoU | 77.78% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | CPS (DeepLab v3+ with ImageNet-pretrained ResNet-101, single scale inference) | https://arxiv.org/abs/2106.01226v2 | Validation mIoU | 77.62% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | n-CPS (ResNet-50) | https://arxiv.org/abs/2112.07528v4 | Validation mIoU | 77.61% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | CW-BASS (DeepLab v3+ with ResNet-50) | https://arxiv.org/abs/2502.15152v1 | Validation mIoU | 77.20% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | PS-MT (DeepLab v3+ with ImageNet-pretrained ResNet50, single scale inference) | https://arxiv.org/abs/2111.12903v3 | Validation mIoU | 77.12% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | LaserMix (DeepLab v3+, ImageNet pre-trained ResNet50, single scale inference) | https://arxiv.org/abs/2207.00026v4 | Validation mIoU | 77.1% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | U2PL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K, AEL) | https://arxiv.org/abs/2203.03884v2 | Validation mIoU | 76.48% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | PCR (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K) | https://arxiv.org/abs/2210.04388v1 | Validation mIoU | 76.31% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | CPCL (DeepLab v3+ with ResNet-50) | https://arxiv.org/abs/2211.16701v2 | Validation mIoU | 74.6% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | SimpleBaseline(DeeplabV3+ with ImageNet pretrained Xception65, sinle scale inference) | https://arxiv.org/abs/2104.07256v4 | Validation mIoU | 74.1% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | Dense FixMatch (DeepLabv3+ ResNet-101, uniform sampling, single pass eval) | https://arxiv.org/abs/2210.09919v1 | Validation mIoU | 73.91% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | Dense FixMatch (DeepLabv3+ ResNet-50, uniform sampling, single pass eval) | https://arxiv.org/abs/2210.09919v1 | Validation mIoU | 73.39% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | Error Localization Network (DeeplabV3 with ResNet-50) | https://arxiv.org/abs/2204.02078v3 | Validation mIoU | 70.33% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | SegSDE (MTL decoder with ResNet101, ImageNet pretrained, unlabeled image sequences) | https://arxiv.org/abs/2012.10782v2 | Validation mIoU | 68.01% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | ReCo (DeepLab v3+ with ResNet-101 backbone, ImageNet pretrained) | https://arxiv.org/abs/2104.04465v4 | Validation mIoU | 66.44% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | GuidedMix-Net(DeepLab v2 with ResNet101, ImageNet pretrained) | https://arxiv.org/abs/2106.15064v2 | Validation mIoU | 65.8% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | ReCo (DeepLab v2 with ResNet-101 backbone, ImageNet pretrained) | https://arxiv.org/abs/2104.04465v4 | Validation mIoU | 64.94% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | SemiSegContrast
(DeepLab v2 with ResNet-101 backbone, MSCOCO pretrained) | https://arxiv.org/abs/2104.13415v3 | Validation mIoU | 64.4% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | DMT (DeepLab v2 MSCOCO/ImageNet pre-trained) | https://arxiv.org/abs/2004.08514v4 | Validation mIoU | 63.03% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | GIST and RIST (DeepLabv2 with ResNet101, MSCOCO pre-trained) | https://arxiv.org/abs/2103.17105v3 | Validation mIoU | 62.57% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | ClassMix (DeepLab v2 MSCOCO pretrained) | https://arxiv.org/abs/2007.07936v2 | Validation mIoU | 61.35% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | CutMix (DeepLab v2, ImageNet pre-trained) | https://arxiv.org/abs/1906.01916v5 | Validation mIoU | 60.34% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | s4GAN (DeepLab v2 ImageNet pre-trained) | https://arxiv.org/abs/1908.05724v1 | Validation mIoU | 59.3% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Cityscapes 12.5% labeled | Adversarial (DeepLab v2 ImageNet pre-trained) | http://arxiv.org/abs/1802.07934v2 | Validation mIoU | 57.1% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | SemiVL | https://arxiv.org/abs/2311.16241v1 | Validation mIoU | 50.1 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | UniMatch V2 | https://arxiv.org/abs/2410.10777v2 | Validation mIoU | 47.9 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | AllSpark | https://arxiv.org/abs/2403.01818v3 | Validation mIoU | 34.10 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | LogicDiag | https://arxiv.org/abs/2308.12595v1 | Validation mIoU | 33.1 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | S4MC | https://arxiv.org/abs/2308.13900v2 | Validation mIoU | 32.9 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | UniMatch | https://arxiv.org/abs/2208.09910v2 | Validation mIoU | 31.9 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | PC2Seg | https://arxiv.org/abs/2108.09025v1 | Validation mIoU | 29.9 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/512 labeled | PseudoSeg | https://arxiv.org/abs/2010.09713v2 | Validation mIoU | 29.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Voxel) | https://arxiv.org/abs/2207.00026v4 | mIoU (1% Labels) | 44.2 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Voxel) | https://arxiv.org/abs/2207.00026v4 | mIoU (10% Labels) | 53.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Voxel) | https://arxiv.org/abs/2207.00026v4 | mIoU (20% Labels) | 55.1 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Voxel) | https://arxiv.org/abs/2207.00026v4 | mIoU (50% Labels) | 56.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Voxel) | http://arxiv.org/abs/1703.01780v6 | mIoU (1% Labels) | 41.0 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Voxel) | http://arxiv.org/abs/1703.01780v6 | mIoU (10% Labels) | 50.1 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Voxel) | http://arxiv.org/abs/1703.01780v6 | mIoU (20% Labels) | 52.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Voxel) | http://arxiv.org/abs/1703.01780v6 | mIoU (50% Labels) | 53.9 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Voxel) | https://arxiv.org/abs/2011.10033v1 | mIoU (1% Labels) | 39.2 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Voxel) | https://arxiv.org/abs/2011.10033v1 | mIoU (10% Labels) | 48.0 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Voxel) | https://arxiv.org/abs/2011.10033v1 | mIoU (20% Labels) | 52.1 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Voxel) | https://arxiv.org/abs/2011.10033v1 | mIoU (50% Labels) | 53.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Range View) | https://arxiv.org/abs/2207.00026v4 | mIoU (1% Labels) | 38.3 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Range View) | https://arxiv.org/abs/2207.00026v4 | mIoU (10% Labels) | 54.4 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Range View) | https://arxiv.org/abs/2207.00026v4 | mIoU (20% Labels) | 55.6 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | LaserMix (Range View) | https://arxiv.org/abs/2207.00026v4 | mIoU (50% Labels) | 58.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CutMix-Seg (Range View) | https://arxiv.org/abs/1906.01916v5 | mIoU (1% Labels) | 36.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CutMix-Seg (Range View) | https://arxiv.org/abs/1906.01916v5 | mIoU (10% Labels) | 50.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CutMix-Seg (Range View) | https://arxiv.org/abs/1906.01916v5 | mIoU (20% Labels) | 52.9 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CutMix-Seg (Range View) | https://arxiv.org/abs/1906.01916v5 | mIoU (50% Labels) | 54.3 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CBST (Range View) | http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Zou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html | mIoU (1% Labels) | 35.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CBST (Range View) | http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Zou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html | mIoU (10% Labels) | 50.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CBST (Range View) | http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Zou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html | mIoU (20% Labels) | 52.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CBST (Range View) | http://openaccess.thecvf.com/content_ECCV_2018/html/Yang_Zou_Unsupervised_Domain_Adaptation_ECCV_2018_paper.html | mIoU (50% Labels) | 54.6 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Range View) | http://arxiv.org/abs/1703.01780v6 | mIoU (1% Labels) | 34.2 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Range View) | http://arxiv.org/abs/1703.01780v6 | mIoU (10% Labels) | 49.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Range View) | http://arxiv.org/abs/1703.01780v6 | mIoU (20% Labels) | 51.6 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | MeanTeacher (Range View) | http://arxiv.org/abs/1703.01780v6 | mIoU (50% Labels) | 53.3 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CPS (Range View) | https://arxiv.org/abs/2106.01226v2 | mIoU (1% Labels) | 33.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CPS (Range View) | https://arxiv.org/abs/2106.01226v2 | mIoU (10% Labels) | 50.0 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CPS (Range View) | https://arxiv.org/abs/2106.01226v2 | mIoU (20% Labels) | 52.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | CPS (Range View) | https://arxiv.org/abs/2106.01226v2 | mIoU (50% Labels) | 54.6 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Range View) | https://arxiv.org/abs/2109.03787v1 | mIoU (1% Labels) | 33.1 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Range View) | https://arxiv.org/abs/2109.03787v1 | mIoU (10% Labels) | 47.7 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Range View) | https://arxiv.org/abs/2109.03787v1 | mIoU (20% Labels) | 49.9 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | ScribbleKITTI | Sup.-only (Range View) | https://arxiv.org/abs/2109.03787v1 | mIoU (50% Labels) | 52.5 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | S4MC | https://arxiv.org/abs/2308.13900v2 | Validation mIoU | 81.11 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | PCR (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K) | https://arxiv.org/abs/2210.04388v1 | Validation mIoU | 80.91% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | U2PL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K, CutMix) | https://arxiv.org/abs/2203.03884v2 | Validation mIoU | 80.5% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | AEL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K) | https://arxiv.org/abs/2110.05474v1 | Validation mIoU | 80.29% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | n-CPS (ResNet-101) | https://arxiv.org/abs/2112.07528v4 | Validation mIoU | 80.26% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | PS-MT
(DeepLab v3+ with ImageNet-pretrained ResNet-101, single scale inference) | https://arxiv.org/abs/2111.12903v3 | Validation mIoU | 79.76% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | GuidedMix-Net(DeepLab v2 with ResNet101, input-size: 512x512 with multi-scale and flip, ImageNet pretrained) | https://arxiv.org/abs/2106.15064v2 | Validation mIoU | 78.2% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | CPCL (DeepLab v3+ with ResNet-101) | https://arxiv.org/abs/2211.16701v2 | Validation mIoU | 77.67% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | PCT (DeepLab v3+ with ResNet-50 pretrained on ImageNet-1K) | https://www.sciencedirect.com/science/article/pii/S003132032200406X | Validation mIoU | 77.26% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | n-CPS (ResNet-50) | https://arxiv.org/abs/2112.07528v4 | Validation mIoU | 77.07% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | GuidedMix-Net(DeepLab v2 with ResNet101, ImageNet pretrained) | https://arxiv.org/abs/2106.15064v2 | Validation mIoU | 76.5% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | CPCL (DeepLab v3+ with ResNet-50) | https://arxiv.org/abs/2211.16701v2 | Validation mIoU | 75.3% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | Dense FixMatch (DeepLabv3+ ResNet-101, over-sampling, single pass eval) | https://arxiv.org/abs/2210.09919v1 | Validation mIoU | 74.73% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | PASCAL VOC 2012 50% | Dense FixMatch (DeepLabv3+ ResNet-50, over-sampling, single pass eval) | https://arxiv.org/abs/2210.09919v1 | Validation mIoU | 71.69% |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Pascal VOC 2012 50% labeled | AllSpark | https://arxiv.org/abs/2403.01818v3 | Validation mIoU | 81.13 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Pascal VOC 2012 50% labeled | FARCLUSS | https://arxiv.org/abs/2506.11142v2 | Validation mIoU | 80.3 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | Pascal VOC 2012 50% labeled | CW-BASS (DeepLab v3+ with ResNet-50) | https://arxiv.org/abs/2502.15152v1 | Validation mIoU | 77.15 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/256 labeled | UniMatch V2 | https://arxiv.org/abs/2410.10777v2 | Validation mIoU | 55.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/256 labeled | SemiVL | https://arxiv.org/abs/2311.16241v1 | Validation mIoU | 52.8 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/256 labeled | AllSpark | https://arxiv.org/abs/2403.01818v3 | Validation mIoU | 41.65 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/256 labeled | S4MC | https://arxiv.org/abs/2308.13900v2 | Validation mIoU | 40.4 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/256 labeled | LogicDiag | https://arxiv.org/abs/2308.12595v1 | Validation mIoU | 40.3 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/256 labeled | PrevMatch | https://arxiv.org/abs/2405.20610v1 | Validation mIoU | 40.2 |
10-shot image generation > Semantic Segmentation > Semi-Supervised Semantic Segmentation | COCO 1/256 labeled | UniMatch | https://arxiv.org/abs/2208.09910v2 | Validation mIoU | 38.9 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.