A Texture Simulation Technique for Textile Exhibition and Design
Bibliographic record
Abstract
ue for the simulation of soft and flexible objects such as textileIn this paper, we propose a texture simulation techniqproducts. This grid acts as the intermediate space between planar space and texture space. Since users can interactivelybuild and modify the texture grid, the target object can be simulated flexibly. Compared with the traditional texturesimulation techniques for polygonal models, the technique dramatically reduces the computation and storage insimulation process, as it is image based. Another advantage of the technique is the simply of using especially foramateur users in comparison with the transitional techniques using polygonal models. In our implementation, user mayneed to adjust the texture grid locally to simulate the special effect such as wrinkles on the clothes. And thecolor-blending process used in this work was considered to be adequate in simulating realistic and pleasing effect for thetextile.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".