Proceedings of the 5th international symposium on Non-photorealistic animation and rendering
Bibliographic record
Abstract
Welcome to NPAR 2007, the fifth meeting of the International Symposium on Non-Photorealistic Animation and Rendering. For the first time in 2007 the symposium is co-located with SIGGRAPH and is being held August 4-5, 2007 in San Diego, California. Once again NPAR will bring together researchers and practitioners to showcase cutting-edge research in non-photorealistic animation and rendering systems and techniques. After the submission deadline in April, we assigned each of the 34 submissions to three committee members. At the end of the review period, committee members reached a consensus decision for each submission based on their initial reviews and an open discussion with additional committee members as needed. We settled upon the final set of 16 papers collected in this volume. Non-photorealistic animation and rendering (NPAR) refers to techniques for visually communicating ideas and information. Such techniques usually generate imagery which is expressive, rather than photorealistic. The papers in this volume present new research on both the mechanisms of non-photorealistic animation and rendering techniques as well as principles of visual communication via such artistic animation and rendering.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.129 | 0.041 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".