Papers › SeMask: Semantically Masked Transformers for Semantic Segmentation
SeMask: Semantically Masked Transformers for Semantic Segmentation
Jitesh Jain, Anukriti Singh, Nikita Orlov, Zilong Huang, Jiachen Li, Steven Walton, Humphrey Shi
Finetuning a pretrained backbone in the encoder part of an image transformer network has been the traditional approach for the semantic segmentation task. However, such an approach leaves out the semantic context that an image provides during the encoding stage. This paper argues that incorporating semantic information of the image into pretrained hierarchical transformer-based backbones while finetuning improves the performance considerably. To achieve this, we propose SeMask, a simple and effective framework that incorporates semantic information into the encoder with the help of a semantic attention operation. In addition, we use a lightweight semantic decoder during training to provide supervision to the intermediate semantic prior maps at every stage. Our experiments demonstrate that incorporating semantic priors enhances the performance of the established hierarchical encoders with a slight increase in the number of FLOPs. We provide empirical proof by integrating SeMask into Swin Transformer and Mix Transformer backbones as our encoder paired with different decoders. Our framework achieves a new state-of-the-art of 58.25% mIoU on the ADE20K dataset and improvements of over 3% in the mIoU metric on the Cityscapes dataset. The code and checkpoints are publicly available at https://github.com/Picsart-AI-Research/SeMask-Segmentation .
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-L FaPN-Mask2Former) | Validation mIoU | 58.2 | #23 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-L MSFaPN-Mask2Former) | Validation mIoU | 58.2 | #24 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-L Mask2Former) | Validation mIoU | 57.5 | #32 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask(SeMask Swin-L MSFaPN-Mask2Former, single-scale) | Validation mIoU | 57.0 | #36 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-L MaskFormer) | Validation mIoU | 56.2 | #41 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-L FPN) | Validation mIoU | 53.52 | #79 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-B FPN) | Params (M) | 96 | #106 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-B FPN) | Validation mIoU | 50.98 | #106 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-S FPN) | Params (M) | 56 | #159 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-S FPN) | Validation mIoU | 47.63 | #159 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-T FPN) | Params (M) | 35 | #211 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | SeMask (SeMask Swin-T FPN) | Validation mIoU | 43.16 | #211 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K val | SeMask (SeMask Swin-L FaPN-Mask2Former) | mIoU | 58.2 | #15 of 95 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K val | SeMask (SeMask Swin-L MSFaPN-Mask2Former) | mIoU | 58.2 | #16 of 95 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K val | SeMask (SeMask Swin-L Mask2Former) | mIoU | 57.5 | #20 of 95 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K val | SeMask (SeMask Swin-L MSFaPN-Mask2Former, single-scale) | mIoU | 57.0 | #23 of 95 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K val | SeMask (SeMask Swin-L MaskFormer) | mIoU | 56.2 | #26 of 95 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K val | SeMask (SeMask Swin-L FPN) | mIoU | 53.5 | #40 of 95 | Archive leaderboard | report |
| Semantic Segmentation | Cityscapes val | SeMask (SeMask Swin-L Mask2Former) | mIoU | 84.98 | #11 of 99 | Archive leaderboard | report |
| Semantic Segmentation | Cityscapes val | SeMask (SeMask Swin-L FPN) | mIoU | 80.39 | #51 of 99 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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