Single-Shot Monocular RGB-D Imaging Using Uneven Double Refraction
Why this work is in the frame
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Bibliographic record
Abstract
Cameras that capture color and depth information have become an essential imaging modality for applications in robotics, autonomous driving, virtual, and augmented reality. Existing RGB-D cameras rely on multiple sensors or active illumination with specialized sensors. In this work, we propose a method for monocular single-shot RGB-D imaging. Instead of learning depth from single-image depth cues, we revisit double-refraction imaging using a birefractive medium, measuring depth as the displacement of differently refracted images superimposed in a single capture. However, existing double-refraction methods are orders of magnitudes too slow to be used in real-time applications, e.g., in robotics, and provide only inaccurate depth due to correspondence ambiguity in double reflection. We resolve this ambiguity optically by leveraging the orthogonality of the two linearly polarized rays in double refraction -- introducing uneven double refraction by adding a linear polarizer to the birefractive medium. Doing so makes it possible to develop a real-time method for reconstructing sparse depth and color simultaneously in real-time. We validate the proposed method, both synthetically and experimentally, and demonstrate 3D object detection and photographic applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it