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 | Cityscapes val | FAN-L-Hybrid | https://arxiv.org/abs/2204.12451v4 | mIoU | 82.3 |
10-shot image generation > Semantic Segmentation | Cityscapes val | SETR-PUP (80k, MS) | https://arxiv.org/abs/2012.15840v3 | mIoU | 82.15 |
10-shot image generation > Semantic Segmentation | Cityscapes val | DSNet-Base(single-scale) | https://arxiv.org/abs/2406.03702v1 | mIoU | 82.0 |
10-shot image generation > Semantic Segmentation | Cityscapes val | EANet | https://arxiv.org/abs/2105.02358v2 | mIoU | 81.7% |
10-shot image generation > Semantic Segmentation | Cityscapes val | HRViT-b1 (SegFormer, SS) | https://arxiv.org/abs/2111.01236v2 | mIoU | 81.63% |
10-shot image generation > Semantic Segmentation | Cityscapes val | CMX (B2) | https://arxiv.org/abs/2203.04838v5 | mIoU | 81.6 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Trans4Trans | https://arxiv.org/abs/2108.09174v1 | mIoU | 81.54% |
10-shot image generation > Semantic Segmentation | Cityscapes val | Panoptic-DeepLab | https://arxiv.org/abs/1911.10194v3 | mIoU | 81.5% |
10-shot image generation > Semantic Segmentation | Cityscapes val | Soft Labells (Deeplab) | null | mIoU | 81.5 |
10-shot image generation > Semantic Segmentation | Cityscapes val | HRNetV2 (HRNetV2-W48) | https://arxiv.org/abs/1908.07919v2 | mIoU | 81.1 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Trans4PASS (Small) | https://arxiv.org/abs/2203.01452v2 | mIoU | 81.1% |
10-shot image generation > Semantic Segmentation | Cityscapes val | DEPICT-SA (ViT-L multi-scale) | https://arxiv.org/abs/2411.03033v3 | mIoU | 81.0 |
10-shot image generation > Semantic Segmentation | Cityscapes val | OCR (ResNet-101-FCN) | https://arxiv.org/abs/1909.11065v6 | mIoU | 80.6 |
10-shot image generation > Semantic Segmentation | Cityscapes val | RepVGG-B2 | https://arxiv.org/abs/2101.03697v3 | mIoU | 80.57% |
10-shot image generation > Semantic Segmentation | Cityscapes val | DSNet(single-scale) | https://arxiv.org/abs/2406.03702v1 | mIoU | 80.4 |
10-shot image generation > Semantic Segmentation | Cityscapes val | DSNet(single-scale) | https://arxiv.org/abs/2406.03702v1 | FPS | 81.9 |
10-shot image generation > Semantic Segmentation | Cityscapes val | SeMask (SeMask Swin-L FPN) | https://arxiv.org/abs/2112.12782v3 | mIoU | 80.39 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Auto-DeepLab-L | http://arxiv.org/abs/1901.02985v2 | mIoU | 80.33% |
10-shot image generation > Semantic Segmentation | Cityscapes val | SML | https://arxiv.org/abs/2107.11264v4 | mIoU | 80.33 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Multiscale DEQ (MDEQ-XL) | https://arxiv.org/abs/2006.08656v2 | mIoU | 80.3% |
10-shot image generation > Semantic Segmentation | Cityscapes val | HRNetV2 (HRNetV2-W40) | https://arxiv.org/abs/1908.07919v2 | mIoU | 80.2 |
10-shot image generation > Semantic Segmentation | Cityscapes val | PSPNet (Dilated-ResNet-101) | http://arxiv.org/abs/1612.01105v2 | mIoU | 79.7 |
10-shot image generation > Semantic Segmentation | Cityscapes val | DeepLabv3+ (Dilated-Xception-71) | http://arxiv.org/abs/1802.02611v3 | mIoU | 79.6 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Trans4PASS (Tiny) | https://arxiv.org/abs/2203.01452v2 | mIoU | 79.1% |
10-shot image generation > Semantic Segmentation | Cityscapes val | DEPICT-SA (ViT-L single-scale) | https://arxiv.org/abs/2411.03033v3 | mIoU | 78.8 |
10-shot image generation > Semantic Segmentation | Cityscapes val | SemanticFPN P2-P5 + PointRend | https://arxiv.org/abs/1912.08193v2 | mIoU | 78.6 |
10-shot image generation > Semantic Segmentation | Cityscapes val | DeepLabv3 (Dilated-ResNet-101) | http://arxiv.org/abs/1706.05587v3 | mIoU | 78.5% |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (8 iterations) | https://arxiv.org/abs/2204.13492v4 | mIoU | 78.2 |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (8 iterations) | https://arxiv.org/abs/2204.13492v4 | FPS | 1.1 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Multiscale DEQ (MDEQ-large) | https://arxiv.org/abs/2006.08656v2 | mIoU | 77.8% |
10-shot image generation > Semantic Segmentation | Cityscapes val | HALO | https://arxiv.org/abs/2306.11180v5 | mIoU | 77.8 |
10-shot image generation > Semantic Segmentation | Cityscapes val | DetCon_B | https://arxiv.org/abs/2103.10957v2 | mIoU | 77.0% |
10-shot image generation > Semantic Segmentation | Cityscapes val | EEEA-Net-C2 (ours) | https://arxiv.org/abs/2108.06156v1 | mIoU | 76.8 |
10-shot image generation > Semantic Segmentation | Cityscapes val | WaveMixLite-256/16 | https://openreview.net/forum?id=y_icnxeeUcl | mIoU | 76.79 |
10-shot image generation > Semantic Segmentation | Cityscapes val | SwinMTL | https://arxiv.org/abs/2403.10662v1 | mIoU | 76.41 |
10-shot image generation > Semantic Segmentation | Cityscapes val | CSFNet-2 | https://arxiv.org/abs/2407.01328v1 | mIoU | 76.36 |
10-shot image generation > Semantic Segmentation | Cityscapes val | CSFNet-2 | https://arxiv.org/abs/2407.01328v1 | FPS | 72.3 (3090) |
10-shot image generation > Semantic Segmentation | Cityscapes val | RepMLPNet-D256 | https://arxiv.org/abs/2112.11081v2 | mIoU | 76.27 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Dilated-ResNet (Dilated-ResNet-101) | http://arxiv.org/abs/1512.03385v1 | mIoU | 75.7 |
10-shot image generation > Semantic Segmentation | Cityscapes val | UNet++ (ResNet-101) | http://arxiv.org/abs/1807.10165v1 | mIoU | 75.5 |
10-shot image generation > Semantic Segmentation | Cityscapes val | SqueezeNAS (LAT XLarge) | https://arxiv.org/abs/1908.01748v2 | mIoU | 75.2% |
10-shot image generation > Semantic Segmentation | Cityscapes val | ReLICv2 | https://arxiv.org/abs/2201.05119v2 | mIoU | 75.2 |
10-shot image generation > Semantic Segmentation | Cityscapes val | CSFNet-1 | https://arxiv.org/abs/2407.01328v1 | mIoU | 74.73 |
10-shot image generation > Semantic Segmentation | Cityscapes val | CSFNet-1 | https://arxiv.org/abs/2407.01328v1 | FPS | 106.1 (3090) |
10-shot image generation > Semantic Segmentation | Cityscapes val | GSCNN (ResNet-101) | https://arxiv.org/abs/1907.05740v1 | mIoU | 74.7% |
10-shot image generation > Semantic Segmentation | Cityscapes val | BYOL | https://arxiv.org/abs/2201.05119v2 | mIoU | 74.6 |
10-shot image generation > Semantic Segmentation | Cityscapes val | WASPnet (ours) | https://arxiv.org/abs/1912.03183v1 | mIoU | 74% |
10-shot image generation > Semantic Segmentation | Cityscapes val | SqueezeNAS (LAT Large) | https://arxiv.org/abs/1908.01748v2 | mIoU | 73.6% |
10-shot image generation > Semantic Segmentation | Cityscapes val | FasterSeg | https://arxiv.org/abs/1912.10917v2 | mIoU | 73.1% |
10-shot image generation > Semantic Segmentation | Cityscapes val | GSCNN (ResNet-50) | https://arxiv.org/abs/1907.05740v1 | mIoU | 73.0% |
10-shot image generation > Semantic Segmentation | Cityscapes val | Aerial-PASS (ResNet-18) | https://arxiv.org/abs/2105.07209v1 | mIoU | 72.8% |
10-shot image generation > Semantic Segmentation | Cityscapes val | RFNet (ResNet-18) | https://arxiv.org/abs/2002.10570v2 | mIoU | 72.5% |
10-shot image generation > Semantic Segmentation | Cityscapes val | ERFNet (PyTorch) | https://ieeexplore.ieee.org/abstract/document/8063438 | mIoU | 72.1% |
10-shot image generation > Semantic Segmentation | Cityscapes val | SwaftNet (ResNet-18) | https://arxiv.org/abs/1909.07721v2 | mIoU | 72.1% |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (4 iterations) | https://arxiv.org/abs/2204.13492v4 | mIoU | 71.5 |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (4 iterations) | https://arxiv.org/abs/2204.13492v4 | FPS | 1.9 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Template-Based NAS-arch1 | https://arxiv.org/abs/1904.02365v2 | mIoU | 69.5% |
10-shot image generation > Semantic Segmentation | Cityscapes val | Fast-SCNN + Coarse + ImageNet | http://arxiv.org/abs/1902.04502v1 | mIoU | 69.19 |
10-shot image generation > Semantic Segmentation | Cityscapes val | LDFNet | https://arxiv.org/abs/1809.09077v3 | mIoU | 68.48% |
10-shot image generation > Semantic Segmentation | Cityscapes val | Template-Based NAS-arch0 | https://arxiv.org/abs/1904.02365v2 | mIoU | 68.1% |
10-shot image generation > Semantic Segmentation | Cityscapes val | SqueezeNAS (LAT Small) | https://arxiv.org/abs/1908.01748v2 | mIoU | 68.0% |
10-shot image generation > Semantic Segmentation | Cityscapes val | ContextNet | http://arxiv.org/abs/1805.04554v4 | mIoU | 65.9% |
10-shot image generation > Semantic Segmentation | Cityscapes val | DiCENet | https://arxiv.org/abs/1906.03516v3 | mIoU | 63.4 |
10-shot image generation > Semantic Segmentation | Cityscapes val | DCT-EDANet | https://arxiv.org/abs/1907.10015v2 | mIoU | 61.6 |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (2 iterations) | https://arxiv.org/abs/2204.13492v4 | mIoU | 57.9 |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (2 iterations) | https://arxiv.org/abs/2204.13492v4 | FPS | 2.9 |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (1 iterations) | https://arxiv.org/abs/2204.13492v4 | mIoU | 45.5 |
10-shot image generation > Semantic Segmentation | Cityscapes val | StreamDEQ (1 iterations) | https://arxiv.org/abs/2204.13492v4 | FPS | 4.3 |
10-shot image generation > Semantic Segmentation | Cityscapes val | MRFP+(Ours) Resnet50 | https://arxiv.org/abs/2311.18331v2 | mIoU | 42.4 |
10-shot image generation > Semantic Segmentation | Cityscapes val | Resnet50 | https://arxiv.org/abs/2311.18331v2 | mIoU | 34.66 |
10-shot image generation > Semantic Segmentation | Cityscapes val | SegFormer-B0 | https://arxiv.org/abs/2105.15203v3 | Validation mIoU | 76.2 |
10-shot image generation > Semantic Segmentation | MCubeS | StitchFusion (RGB-A-D-N) | https://arxiv.org/abs/2408.01343v1 | mIoU | 53.92 |
10-shot image generation > Semantic Segmentation | MCubeS | StitchFusion (RGB-A-D) | https://arxiv.org/abs/2408.01343v1 | mIoU | 53.26 |
10-shot image generation > Semantic Segmentation | MCubeS | StitchFusion (RGB-N) | https://arxiv.org/abs/2408.01343v1 | mIoU | 53.21 |
10-shot image generation > Semantic Segmentation | MCubeS | MMSFormer (RGB-A-D-N) | https://arxiv.org/abs/2309.04001v4 | mIoU | 53.11% |
10-shot image generation > Semantic Segmentation | MCubeS | MemorySAM-B+(RGB-A-D-N) | https://arxiv.org/abs/2503.06700v1 | mIoU | 52.88 |
10-shot image generation > Semantic Segmentation | MCubeS | StitchFusion (RGB-D) | https://arxiv.org/abs/2408.01343v1 | mIoU | 52.72 |
10-shot image generation > Semantic Segmentation | MCubeS | StitchFusion (RGB-A) | https://arxiv.org/abs/2408.01343v1 | mIoU | 52.68 |
10-shot image generation > Semantic Segmentation | MCubeS | MemorySAM-B+(RGB-A-D) | https://arxiv.org/abs/2503.06700v1 | mIoU | 52.20 |
10-shot image generation > Semantic Segmentation | MCubeS | MMSFormer (RGB-A-D) | https://arxiv.org/abs/2309.04001v4 | mIoU | 52.05% |
10-shot image generation > Semantic Segmentation | MCubeS | CMNeXt (B2 RGB-A-D-N) | https://arxiv.org/abs/2303.01480v1 | mIoU | 51.54% |
10-shot image generation > Semantic Segmentation | MCubeS | MMSFormer (RGB-A) | https://arxiv.org/abs/2309.04001v4 | mIoU | 51.30% |
10-shot image generation > Semantic Segmentation | MCubeS | MemorySAM-B+(RGB-A) | https://arxiv.org/abs/2503.06700v1 | mIoU | 51.20 |
10-shot image generation > Semantic Segmentation | MCubeS | ShareCMP (B2 RGB-A-D) | https://arxiv.org/abs/2312.03430v2 | mIoU | 50.99% |
10-shot image generation > Semantic Segmentation | MCubeS | ShareCMP(B2 RGB-D) | https://arxiv.org/abs/2312.03430v2 | mIoU | 50.55 |
10-shot image generation > Semantic Segmentation | MCubeS | MMSFormer (RGB) | https://arxiv.org/abs/2309.04001v4 | mIoU | 50.44% |
10-shot image generation > Semantic Segmentation | MCubeS | ShareCMP(B2 RGB-A) | https://arxiv.org/abs/2312.03430v2 | mIoU | 50.34 |
10-shot image generation > Semantic Segmentation | MCubeS | CMNeXt (B2 RGB-A-D) | https://arxiv.org/abs/2303.01480v1 | mIoU | 49.48% |
10-shot image generation > Semantic Segmentation | MCubeS | CMNeXt (B2 RGB-A) | https://arxiv.org/abs/2303.01480v1 | mIoU | 48.42% |
10-shot image generation > Semantic Segmentation | MCubeS | MCubeSNet (RGB-A-D-N) | http://openaccess.thecvf.com//content/CVPR2022/html/Liang_Multimodal_Material_Segmentation_CVPR_2022_paper.html | mIoU | 42.86% |
10-shot image generation > Semantic Segmentation | MCubeS | DeepLabV3+ (RGB-A-D-N) | http://arxiv.org/abs/1802.02611v3 | mIoU | 38.13% |
10-shot image generation > Semantic Segmentation | MCubeS | DDF (RGB-A-D-N) | https://arxiv.org/abs/2104.14107v1 | mIoU | 36.16% |
10-shot image generation > Semantic Segmentation | MCubeS | DRConv (RGB-A-D-N) | https://arxiv.org/abs/2003.12243v3 | mIoU | 34.63% |
10-shot image generation > Semantic Segmentation | WildDash | SIW | https://arxiv.org/abs/2202.02002v2 | Mean IoU | 69.7 |
10-shot image generation > Semantic Segmentation | LandCover.ai | U-Net (ConvFormer-M36) | https://www.mdpi.com/2072-4292/16/12/2077 | mIoU | 87.64 |
10-shot image generation > Semantic Segmentation | BDD100K val | VLTSeg | https://arxiv.org/abs/2312.02021v4 | mIoU | 72.5 |
10-shot image generation > Semantic Segmentation | BDD100K val | SERNet-Former_v2 | https://arxiv.org/abs/2401.15741v7 | mIoU | 67.42 |
10-shot image generation > Semantic Segmentation | BDD100K val | DSNet-Base | https://arxiv.org/abs/2406.03702v1 | mIoU | 64.6 |
10-shot image generation > Semantic Segmentation | BDD100K val | Deeplabv3+ | http://arxiv.org/abs/1802.02611v3 | mIoU | 63.6 |
10-shot image generation > Semantic Segmentation | BDD100K val | DANet | http://arxiv.org/abs/1809.02983v4 | mIoU | 62.8 |
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