GeomPrompt learns a task-driven geometric prompt from RGB alone to substitute for missing or degraded depth in frozen RGB-D semantic segmentation models, yielding up to +6.1 mIoU gains on SUN RGB-D while being faster than monocular depth estimators.
Improving Feature Stability During Upsampling – Spectral Artifacts and the Importance of Spatial Context
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GeomPrompt: Geometric Prompt Learning for RGB-D Semantic Segmentation Under Missing and Degraded Depth
GeomPrompt learns a task-driven geometric prompt from RGB alone to substitute for missing or degraded depth in frozen RGB-D semantic segmentation models, yielding up to +6.1 mIoU gains on SUN RGB-D while being faster than monocular depth estimators.