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 > Real-Time Semantic Segmentation | Cityscapes test | Template-Based-NAS-arch1 | https://arxiv.org/abs/1904.02365v2 | Frame (fps) | 10 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | Template-Based-NAS-arch0 | https://arxiv.org/abs/1904.02365v2 | mIoU | 67.7% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | Template-Based-NAS-arch0 | https://arxiv.org/abs/1904.02365v2 | Time (ms) | 52 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | Template-Based-NAS-arch0 | https://arxiv.org/abs/1904.02365v2 | Frame (fps) | 19 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | EDANet | https://arxiv.org/abs/1809.06323v3 | mIoU | 67.3 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | EDANet | https://arxiv.org/abs/1809.06323v3 | Time (ms) | 9.2 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | EDANet | https://arxiv.org/abs/1809.06323v3 | Frame (fps) | 108.7 (1080Ti) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | ENet + Lovász-Softmax | http://arxiv.org/abs/1705.08790v2 | mIoU | 63.1% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | ENet + Lovász-Softmax | http://arxiv.org/abs/1705.08790v2 | Time (ms) | 13 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | ENet + Lovász-Softmax | http://arxiv.org/abs/1705.08790v2 | Frame (fps) | 76.9 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | DeepLab | http://arxiv.org/abs/1412.7062v4 | mIoU | 63.1% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | DeepLab | http://arxiv.org/abs/1412.7062v4 | Time (ms) | 4000 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | DeepLab | http://arxiv.org/abs/1412.7062v4 | Frame (fps) | 0.25 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | CRF-RNN | http://arxiv.org/abs/1502.03240v3 | mIoU | 62.5% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | CRF-RNN | http://arxiv.org/abs/1502.03240v3 | Time (ms) | 700 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | CRF-RNN | http://arxiv.org/abs/1502.03240v3 | Frame (fps) | 1.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | ENet | http://arxiv.org/abs/1606.02147v1 | mIoU | 58.3% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | ENet | http://arxiv.org/abs/1606.02147v1 | Time (ms) | 13 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | Cityscapes test | ENet | http://arxiv.org/abs/1606.02147v1 | Frame (fps) | 76.9 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PIDNet-M (Cityscapes-Pretrained) | https://arxiv.org/abs/2206.02066v3 | mIoU | 82.0 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PIDNet-M (Cityscapes-Pretrained) | https://arxiv.org/abs/2206.02066v3 | Time (ms) | 11.7 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PIDNet-M (Cityscapes-Pretrained) | https://arxiv.org/abs/2206.02066v3 | Frame (fps) | 85.6(3090) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | RTFormer-Slim | https://arxiv.org/abs/2210.07124v1 | mIoU | 81.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | RTFormer-Slim | https://arxiv.org/abs/2210.07124v1 | Frame (fps) | 190.7(2080Ti) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | RegSeg(Cityscapes-Pretrained) | https://arxiv.org/abs/2111.09957v3 | mIoU | 80.9 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | RegSeg(Cityscapes-Pretrained) | https://arxiv.org/abs/2111.09957v3 | Time (ms) | 14 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | RegSeg(Cityscapes-Pretrained) | https://arxiv.org/abs/2111.09957v3 | Frame (fps) | 70 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DDRNet-23(Cityscapes-Pretrained) | https://arxiv.org/abs/2101.06085v2 | mIoU | 80.6 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DDRNet-23(Cityscapes-Pretrained) | https://arxiv.org/abs/2101.06085v2 | Time (ms) | 10.6 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DDRNet-23(Cityscapes-Pretrained) | https://arxiv.org/abs/2101.06085v2 | Frame (fps) | 94(2080Ti) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | P2AT-S | https://arxiv.org/abs/2310.15025v1 | mIoU | 80.5 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | P2AT-S | https://arxiv.org/abs/2310.15025v1 | Frame (fps) | 113.6(3090) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PIDNet-S (Cityscapes-Pretrained) | https://arxiv.org/abs/2206.02066v3 | mIoU | 80.1 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PIDNet-S (Cityscapes-Pretrained) | https://arxiv.org/abs/2206.02066v3 | Time (ms) | 6.5 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PIDNet-S (Cityscapes-Pretrained) | https://arxiv.org/abs/2206.02066v3 | Frame (fps) | 153.7(3090) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | HyperSeg-L | https://arxiv.org/abs/2012.11582v2 | mIoU | 79.1 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | HyperSeg-L | https://arxiv.org/abs/2012.11582v2 | Time (ms) | 60.2 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | HyperSeg-L | https://arxiv.org/abs/2012.11582v2 | Frame (fps) | 16.6 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2-Large(Cityscapes-Pretrained) | https://arxiv.org/abs/2004.02147v1 | mIoU | 78.5 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2-Large(Cityscapes-Pretrained) | https://arxiv.org/abs/2004.02147v1 | Time (ms) | 30.6 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2-Large(Cityscapes-Pretrained) | https://arxiv.org/abs/2004.02147v1 | Frame (fps) | 32.7 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | HyperSeg-S | https://arxiv.org/abs/2012.11582v2 | mIoU | 78.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | HyperSeg-S | https://arxiv.org/abs/2012.11582v2 | Time (ms) | 26.3 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | HyperSeg-S | https://arxiv.org/abs/2012.11582v2 | Frame (fps) | 38.0 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2(Cityscapes-Pretrained) | https://arxiv.org/abs/2004.02147v1 | mIoU | 76.7 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2(Cityscapes-Pretrained) | https://arxiv.org/abs/2004.02147v1 | Time (ms) | 8.0 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2(Cityscapes-Pretrained) | https://arxiv.org/abs/2004.02147v1 | Frame (fps) | 124.5 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | TD2-PSP50 | https://arxiv.org/abs/2004.01800v2 | mIoU | 76.0 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | TD2-PSP50 | https://arxiv.org/abs/2004.01800v2 | Time (ms) | 90 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | TD2-PSP50 | https://arxiv.org/abs/2004.01800v2 | Frame (fps) | 11(TitanX) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PP-LiteSeg-B | https://arxiv.org/abs/2204.02681v1 | mIoU | 75 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PP-LiteSeg-B | https://arxiv.org/abs/2204.02681v1 | Frame (fps) | 154.8 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DDRNet-23-slim | https://arxiv.org/abs/2101.06085v2 | mIoU | 74.7 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DDRNet-23-slim | https://arxiv.org/abs/2101.06085v2 | Time (ms) | 4.3 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DDRNet-23-slim | https://arxiv.org/abs/2101.06085v2 | Frame (fps) | 230(2080Ti) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | S^2-FPN34M | https://arxiv.org/abs/2206.07298v3 | mIoU | 74.2 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | Mobile-Seed | https://arxiv.org/abs/2311.12651v3 | mIoU | 73.6% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | Mobile-Seed | https://arxiv.org/abs/2311.12651v3 | Frame (fps) | 32.7 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PP-LiteSeg-T | https://arxiv.org/abs/2204.02681v1 | mIoU | 73.3 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PP-LiteSeg-T | https://arxiv.org/abs/2204.02681v1 | Frame (fps) | 222.3 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2-Large | https://arxiv.org/abs/2004.02147v1 | mIoU | 73.2 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2-Large | https://arxiv.org/abs/2004.02147v1 | Time (ms) | 30.6 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2-Large | https://arxiv.org/abs/2004.02147v1 | Frame (fps) | 32.7 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | TD4-PSP18 | https://arxiv.org/abs/2004.01800v2 | mIoU | 72.6 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | TD4-PSP18 | https://arxiv.org/abs/2004.01800v2 | Time (ms) | 40 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | TD4-PSP18 | https://arxiv.org/abs/2004.01800v2 | Frame (fps) | 25(TitanX) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2 | https://arxiv.org/abs/2004.02147v1 | mIoU | 72.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2 | https://arxiv.org/abs/2004.02147v1 | Time (ms) | 8.0 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet V2 | https://arxiv.org/abs/2004.02147v1 | Frame (fps) | 124.5 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | S^2-FPN34 | https://arxiv.org/abs/2206.07298v3 | mIoU | 71.0 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | S^2-FPN34 | https://arxiv.org/abs/2206.07298v3 | Frame (fps) | 107.2 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | S^2-FPN18 | https://arxiv.org/abs/2206.07298v3 | mIoU | 69.5 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | S^2-FPN18 | https://arxiv.org/abs/2206.07298v3 | Frame (fps) | 124.2 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | BiSeNet | http://arxiv.org/abs/1808.00897v1 | mIoU | 68.7% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | ICNet | http://arxiv.org/abs/1704.08545v2 | mIoU | 67.1% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | ICNet | http://arxiv.org/abs/1704.08545v2 | Time (ms) | 36 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | ICNet | http://arxiv.org/abs/1704.08545v2 | Frame (fps) | 27.8 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | EDANet | https://arxiv.org/abs/1809.06323v3 | mIoU | 66.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | Dilation10 | http://arxiv.org/abs/1511.07122v3 | mIoU | 65.3% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | Dilation10 | http://arxiv.org/abs/1511.07122v3 | Time (ms) | 227 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | Dilation10 | http://arxiv.org/abs/1511.07122v3 | Frame (fps) | 4.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | LMDNet | http://arxiv.org/abs/1809.03994v1 | mIoU | 63.5 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | LMDNet | http://arxiv.org/abs/1809.03994v1 | Time (ms) | 29.1 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | LMDNet | http://arxiv.org/abs/1809.03994v1 | Frame (fps) | 34.4 (1080) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DeepLab | http://arxiv.org/abs/1412.7062v4 | mIoU | 61.6% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DeepLab | http://arxiv.org/abs/1412.7062v4 | Time (ms) | 203 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | DeepLab | http://arxiv.org/abs/1412.7062v4 | Frame (fps) | 4.9 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | SegNet | http://arxiv.org/abs/1511.00561v3 | mIoU | 46.4% |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | SegNet | http://arxiv.org/abs/1511.00561v3 | Time (ms) | 217 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | SegNet | http://arxiv.org/abs/1511.00561v3 | Frame (fps) | 4.6 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PSPNet | http://arxiv.org/abs/1612.01105v2 | Time (ms) | 185.0 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | CamVid | PSPNet | http://arxiv.org/abs/1612.01105v2 | Frame (fps) | 5.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | HelixNet | Helix4D | https://arxiv.org/abs/2206.08194v2 | mIoU (1/5 rotation) | 78.7 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | HelixNet | Helix4D | https://arxiv.org/abs/2206.08194v2 | Inference Time (ms) (1/5 rotation) | 19 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | NYU Depth v2 | AsymFormer | https://arxiv.org/abs/2309.14065v7 | mIoU | 54.1 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | NYU Depth v2 | AsymFormer | https://arxiv.org/abs/2309.14065v7 | Speed(ms/f) | 15.3 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | NYU Depth v2 | AsymFormer | https://arxiv.org/abs/2309.14065v7 | Speed (FPS) | 65.5 (3090) |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | NYU Depth v2 | Light-Weight-RefineNet-152 | http://arxiv.org/abs/1810.03272v1 | mIoU | 44.4 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | NYU Depth v2 | Light-Weight-RefineNet-152 | http://arxiv.org/abs/1810.03272v1 | Speed(ms/f) | 36 |
10-shot image generation > Semantic Segmentation > Real-Time Semantic Segmentation | NYU Depth v2 | Light-Weight-RefineNet-101 | http://arxiv.org/abs/1810.03272v1 | mIoU | 43.6 |
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