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Bending Reality: Distortion-Aware Transformers for Adapting to Panoramic Semantic Segmentation

CVPR 2022 · Detection and segmentation › Open-set and few-shot detection · approach: Domain-adaptive segmentation · 103 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add distortion-aware DPE instead of DPT patch embedding (ablation)Trans4PASS · DensePASSmIoU: 36.50 -> 45.89Helped
Use DMLP rather than CycleMLP in the decoder (ablation)Trans4PASS · DensePASSmIoU: 40.16 -> 45.89Helped
Use DMLP rather than ASMLP in the decoder (ablation)Trans4PASS · DensePASSmIoU: 42.05 -> 45.89Helped
Add a DMLP decoder to the PVT-T encoder (ablation)PVT-T · DensePASSmIoU: 31.20 -> 35.18Helped
Add MPA to Trans4PASS-S adaptation (ablation)Trans4PASS-S · Stanford2D3D-Panoramic fold-1mIoU: 48.34 -> 52.15Helped
Add MPA to Trans4PASS-T adaptation (ablation)Trans4PASS-T · DensePASSmIoU: 45.89 -> 51.93Helped
Add pseudo-label SSL to MPA (ablation)Trans4PASS-T · DensePASSmIoU: 51.93 -> 53.26Helped
Add multi-scale evaluation (ablation)Trans4PASS-S with MPA + SSL · DensePASSmIoU: 55.25 -> 56.38Helped
Set the DPE offset restriction to r=4 rather than no restriction (ablation)Trans4PASS · DensePASSmIoU: 45.74 -> 45.89Helped
Add mutual prototype alignment to source-only adaptation (ablation)Trans4PASS · Stanford2D3D-Panoramic, 3-fold averagemIoU: 48.1 -> 50.8Helped

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