[IROS 2026] Mirage 18k: Dataset for Glass Segmentation & Depth Estimation Mirage 18k is a novel, multi task dataset comprising 18,353 manually annotated images across 38 unique indoor scenes , designed specifically for joint glass segmentation and glass aware monocular depth estimation in robotics. It contains diverse real world glass structures (indoor panes, frosted doors, windows, clear doors) with severe background clutter, saliency, and dynamic obstacles. Model Checkpoint: SILICA Model Card Code Repository: GitHub Repository (rtarun1/Silica) Project Page: silica mirage.github.io Example Data: GitHub example/ Directory This work has been accepted for publication at IROS 2026, as part of the work SILICA: Repurposing Diffusion Priors for Joint Glass Segmentation and Depth Estimation . Dataset Acquisition & Overview Acquisition Protocol Ground truth depth for transparent surfaces is captured by modeling each glass pane as a 3D planar surface. Temporary opaque markers are placed at pane corners, and their median depth is extracted from local neighborhoods. A stationary camera records the scene twice—once with markers to capture accurate depth, and once without markers from the exac…
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