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Cityscapes test Benchmark (Semantic Segmentation)
Over time archive 2025-07-28
The chart needs JavaScript; the table below carries every value.
Direction inferred from the metric name, not from the archive: Mean IoU (class) (higher is better). Not inferred (points only, no best-so-far line): Category mIoU. Points are placed at the row's paper date; 105 of 105 rows carry one.
Results archive 2025-07-28
Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.
| Paper | Code | Ran Syntology | Report | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | VLTSeg | 86.4 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 2 | MetaPrompt-SD | 86.2 | – | Paper | Code | 2023 | 4 of 6 ran · 2 unverified | report | |
| 3 | InternImage-H | 86.1% | – | Paper | Code | 2022 | 2 of 4 ran · 2 unverified | report | |
| 4 | HS3-Fuse | 85.8% | – | Paper | – | 2021 | no code linked | report | |
| 5 | InverseForm | 85.6% | – | Paper | Code | 2021 | 1 of 3 ran · 2 unverified | report | |
| 6 | ViT-Adapter-L (Mask2Former, BEiT pretrain) | 85.2% | – | Paper | Code | 2022 | linked, not harvested | report | |
| 7 | SERNet-Former | 84.83 | – | Paper | Code | 2024 | linked, not harvested | report | |
| 8 | Depth Anything | 84.8% | – | Paper | Code | 2024 | 3 of 11 ran · 8 unverified | report | |
| 9 | HRNetV2 + OCR + | 84.5% | – | Paper | Code | 2019 | 4 of 9 ran · 5 unverified | report | |
| 10 | EfficientPS | 84.21% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 11 | Panoptic-DeepLab | 84.2% | – | Paper | Code | 2019 | 3 of 9 ran · 6 unverified | report | |
| 12 | HRNetV2 + OCR (w/ ASP) | 83.7% | – | Paper | Code | 2019 | 4 of 9 ran · 5 unverified | report | |
| 13 | DCNAS(coarse + Mapillary) | 83.6% | – | Paper | – | 2020 | no code linked | report | |
| 14 | Euclidean Frank-Wolfe CRFs (backbone: DeepLabv3+)(coarse) | 83.6% | – | Paper | Code | 2021 | 4 of 5 ran · 1 unverified | report | |
| 15 | GALDNet(+Mapillary)++ | 83.3% | – | Paper | Code | 2019 | 2 of 4 ran · 2 unverified | report | |
| 16 | ResNeSt200 (Mapillary) | 83.3% | – | Paper | Code | 2020 | 8 of 48 ran · 40 unverified | report | |
| 17 | HANet (Height-driven Attention Networks by LGE A&B)(coarse) | 83.2% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 18 | kMaX-DeepLab (ConvNeXt-L, fine only) | 83.2% | – | Paper | Code | 2022 | linked, not harvested | report | |
| 19 | SegFormer (MiT-B5, Mapillary) | 83.1% | – | Paper | Code | 2021 | 48 of 86 ran · 38 unverified | report | |
| 20 | OCR (HRNetV2-W48, coarse) | 83.0% | – | Paper | Code | 2019 | 4 of 9 ran · 5 unverified | report | |
| 21 | MRFM(coarse) | 83.0% | – | Paper | – | 2020 | no code linked | report | |
| 22 | DNL (coarse) | 83% | – | Paper | Code | 2020 | 1 of 3 ran · 2 unverified | report | |
| 23 | DRAN(ResNet-101) WITH ONLY FINE ANNOTATED DATA | 82.9% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 24 | Gated-SCNN | 82.8% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 25 | Dense Prediction Cell | 82.7% | – | Paper | Code | 2018 | linked, not harvested | report | |
| 26 | CAA (ResNet-101) | 82.6% | – | Paper | Code | 2021 | linked, not harvested | report | |
| 27 | OCR (ResNet-101, coarse) | 82.4% | – | Paper | Code | 2019 | 4 of 9 ran · 5 unverified | report | |
| 28 | DDRNet-39 1.5x | 82.4% | – | Paper | Code | 2021 | linked, not harvested | report | |
| 29 | SSMA | 82.3% | – | Paper | Code | 2018 | linked, not harvested | report | |
| 30 | Gated Fully Fusion | 82.3% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 31 | Auto-DeepLab-L | 82.1% | – | Paper | Code | 2019 | 1 of 4 ran · 3 unverified | report | |
| 32 | DGCNet (ResNet-101) | 82% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 33 | SPNet (ResNet-101) | 82.0% | – | Paper | Code | 2020 | 2 of 11 ran · 9 unverified | report | |
| 34 | OCR (ResNet-101) | 81.8% | – | Paper | Code | 2019 | 4 of 9 ran · 5 unverified | report | |
| 35 | RPCNet | 81.8 | – | Paper | – | 2020 | no code linked | report | |
| 36 | OCNet | 81.7% | – | Paper | Code | 2018 | linked, not harvested | report | |
| 37 | SETR-PUP++ | 81.64% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 38 | HRNet (HRNetV2-W48) | 81.6% | – | Paper | Code | 2019 | 3 of 18 ran · 15 unverified | report | |
| 39 | HRNetV2 (train+val) | 81.6% | – | Paper | Code | 2019 | 3 of 34 ran · 31 unverified | report | |
| 40 | DANet (ResNet-101) | 81.5% | – | Paper | Code | 2018 | 0 of 7 ran · 7 unverified | report | |
| 41 | CCNet | 81.4% | – | Paper | Code | 2018 | 9 of 14 ran · 5 unverified | report | |
| 42 | BFP | 81.4% | – | Paper | Code | 2019 | 1 of 11 ran · 10 unverified | report | |
| 43 | DeepLabv3 (ResNet-101, coarse) | 81.3% | – | Paper | Code | 2017 | 3 of 7 ran · 4 unverified | report | |
| 44 | CPN(ResNet-101) | 81.3% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 45 | Asymmetric ALNN | 81.3% | – | Paper | Code | 2019 | 0 of 3 ran · 3 unverified | report | |
| 46 | AdapNet++ | 81.24% | – | Paper | Code | 2018 | linked, not harvested | report | |
| 47 | SVCNet (ResNet-101) | 81.0% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 48 | D3Net-L | 80.8% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 49 | DenseASPP (DenseNet-161) | 80.6% | – | Paper | Code | 2018 | linked, not harvested | report | |
| 50 | Smooth Network with Channel Attention Block | 80.3% | – | Paper | Code | 2018 | 0 of 8 ran · 8 unverified | report | |
| 51 | PSPNet++ | 80.2% | – | Paper | Code | 2016 | 7 of 29 ran · 22 unverified | report | |
| 52 | PSANet (ResNet-101) | 80.1% | – | Paper | Code | 2018 | linked, not harvested | report | |
| 53 | ESANet-R34-NBt1D | 80.09% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 54 | DeepLabV3 with R-101 | 79.9% | – | Paper | – | 2023 | no code linked | report | |
| 55 | DFN (ResNet-101) | 79.3% | – | Paper | Code | 2018 | 0 of 8 ran · 8 unverified | report | |
| 56 | AAF (ResNet-101) | 79.1% | – | Paper | Code | 2018 | 1 of 1 ran · 0 unverified | report | |
| 57 | ShelfNet-34 | 79.0% | – | Paper | Code | 2018 | linked, not harvested | report | |
| 58 | BiSeNet (ResNet-101) | 78.9% | – | Paper | Code | 2018 | 6 of 18 ran · 12 unverified | report | |
| 59 | ResNet-38 | 78.4% | – | Paper | Code | 2016 | 0 of 2 ran · 2 unverified | report | |
| 60 | PSPNet | 78.4% | – | Paper | Code | 2016 | 7 of 29 ran · 22 unverified | report | |
| 61 | DepthSeg (ResNet-101) | 78.2% | – | Paper | Code | 2017 | linked, not harvested | report | |
| 62 | DSSPN (ResNet-101) | 77.8% | – | Paper | – | 2018 | no code linked | report | |
| 63 | DUC-HDC (ResNet-101) | 77.6% | – | Paper | Code | 2017 | 0 of 1 ran · 1 unverified | report | |
| 64 | SaGe | 76.9 | – | Paper | Code | 2021 | linked, not harvested | report | |
| 65 | SwinMTL | 76.41% | – | Paper | Code | 2024 | linked, not harvested | report | |
| 66 | SwiftNetRN-18 | 75.5% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 67 | RefineNet (ResNet-101) | 73.6% | – | Paper | Code | 2016 | 1 of 7 ran · 6 unverified | report | |
| 68 | MobileNet V3-Large 1.0 | 72.6% | – | Paper | Code | 2019 | 58 of 105 ran · 47 unverified | report | |
| 69 | SqueezeNAS (LAT Large) | 72.5% | – | Paper | Code | 2019 | 0 of 5 ran · 5 unverified | report | |
| 70 | Multi Scale Spatial Attention | 72.4% | – | Paper | – | 2020 | no code linked | report | |
| 71 | FRRN | 71.8% | – | Paper | Code | 2016 | 3 of 3 ran · 0 unverified | report | |
| 72 | LRR-4x | 71.8% | – | Paper | Code | 2016 | linked, not harvested | report | |
| 73 | Context | 71.6% | – | Paper | – | 2015 | no code linked | report | |
| 74 | FasterSeg | 71.5% | – | Paper | Code | 2019 | 2 of 13 ran · 11 unverified | report | |
| 75 | DFANet A | 71.3% | – | Paper | Code | 2019 | 1 of 1 ran · 0 unverified | report | |
| 76 | LDFNet | 71.3 | – | Paper | Code | 2018 | linked, not harvested | report | |
| 77 | LightSeg-DarkNet19 | 70.75% | 88.29 | – | Paper | Code | 2019 | linked, not harvested | report |
| 78 | ESNet | 70.7% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 79 | ICNet | 70.6% | – | Paper | Code | 2017 | linked, not harvested | report | |
| 80 | LEDNet | 70.6% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 81 | WASPnet (ours) | 70.5% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 82 | DeepLab-CRF (ResNet-101) | 70.4% | – | Paper | Code | 2016 | 28 of 63 ran · 35 unverified | report | |
| 83 | ERFNet (PyTorch) | 69.8% | – | Paper | Code | 2017 | linked, not harvested | report | |
| 84 | Fast-SCNN | 68% | – | Paper | Code | 2019 | 0 of 32 ran · 32 unverified | report | |
| 85 | LightSeg-MobileNet | 67.81% | 86.79 | – | Paper | Code | 2019 | linked, not harvested | report |
| 86 | LiteSeg-MobileNet | 67.81% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 87 | Template-Based NAS-arch1 | 67.8% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 88 | Template-Based NAS-arch0 | 67.7% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 89 | EDANet | 67.3 | – | Paper | Code | 2018 | linked, not harvested | report | |
| 90 | Dilation10 | 67.1% | – | Paper | Code | 2015 | 2 of 8 ran · 6 unverified | report | |
| 91 | DPN | 66.8% | – | Paper | Code | 2015 | linked, not harvested | report | |
| 92 | SqueezeNAS (LAT Small) | 66.8% | – | Paper | Code | 2019 | 0 of 5 ran · 5 unverified | report | |
| 93 | SINet | 66.5% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 94 | ESPNetv2 | 66.2% | – | Paper | Code | 2018 | 2 of 4 ran · 2 unverified | report | |
| 95 | FCN | 65.3% | – | Paper | Code | 2016 | linked, not harvested | report | |
| 96 | LightSeg-ShuffleNet | 65.17% | 85.39 | – | Paper | Code | 2019 | linked, not harvested | report |
| 97 | LiteSeg-ShuffleNet | 65.17% | – | Paper | Code | 2019 | linked, not harvested | report | |
| 98 | DeepLab | 63.1% | – | Paper | Code | 2014 | 0 of 1 ran · 1 unverified | report | |
| 99 | ENet + Lovász-Softmax | 63.06% | – | Paper | Code | 2017 | linked, not harvested | report | |
| 100 | ESPNet | 60.3% | – | Paper | Code | 2018 | 4 of 10 ran · 6 unverified | report | |
| 101 | ENet | 58.3% | – | Paper | Code | 2016 | 5 of 30 ran · 25 unverified | report | |
| 102 | SegNet | 57.0% | – | Paper | Code | 2015 | 9 of 44 ran · 35 unverified | report | |
| 103 | IkshanaNet-1 | 54.82% | 82.22% | – | Paper | Code | 2021 | linked, not harvested | report |
| 104 | IkshanaNet-2 | 45.02% | 76.73% | – | Paper | Code | 2021 | linked, not harvested | report |
| 105 | IkshanaNet-3 | 42.07% | 75.61% | – | Paper | Code | 2021 | linked, not harvested | report |
All 105 rows shown. 105 link to a paper page on this site; 0 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28
Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 47 rows have a graph line, from 40 distinct papers; 37 rows (32 papers) have at least one sample that ran. Counting each paper once: Syntology ran 231 of 682 samples; 451 unverified. Separately, 165 of those 682 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.
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