Result-Driven Exploration of Simulation Parameter Spaces for Visual Effects Design
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
Graphics artists commonly employ physically-based simulation for the generation of effects such as smoke, explosions, and similar phenomena. The task of finding the correct parameters for a desired result, however, is difficult and time-consuming as current tools provide little to no guidance. In this paper, we present a new approach for the visual exploration of such parameter spaces. Given a three-dimensional scene description, we utilize sampling and spatio-temporal clustering techniques to generate a concise overview of the achievable variations and their temporal evolution. Our visualization system then allows the user to explore the simulation space in a goal-oriented manner. Animation sequences with a set of desired characteristics can be composed using a novel search-by-example approach and interactive direct volume rendering is employed to provide instant visual feedback. A user study was performed to evaluate the applicability of our system in production use.
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 | 0.001 |
| 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