Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents Rich360, a novel system for creating and viewing a 360° panoramic video obtained from multiple cameras placed on a structured rig. Rich360 provides an as-rich-as-possible 360° viewing experience by effectively resolving two issues that occur in the existing pipeline. First, a deformable spherical projection surface is utilized to minimize the parallax from multiple cameras. The surface is deformed spatio-temporally according to the depth constraints estimated from the overlapping video regions. This enables fast and efficient parallax-free stitching independent of the number of views. Next, a non-uniform spherical ray sampling is performed. The density of the sampling varies depending on the importance of the image region. Finally, for interactive viewing, the non-uniformly sampled video is mapped onto a uniform viewing sphere using a UV map. This approach can preserve the richness of the input videos when the resolution of the final 360° panoramic video is smaller than the overall resolution of the input videos, which is the case for most 360° panoramic videos. We show various results from Rich360 to demonstrate the richness of the output video and the advancement in the stitching results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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