Research of 3D Virtual Characters Reconstructions Based on NeRF
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
With the development of the Internet, Metauniverse, and graphics processing technique, video games and immersive virtual social contacting service are largely propelled. Therefore, the quality of 3D virtual character models is getting more and more important—higher fidelities of screens have largely promoted the demand for finer 3D character models. However, the cost and time efficiency of traditional modeling relied on human artist can hardly support such a great demand, and will potentially slow down the development of video game and metauniverse industry. In an effort to improve this situation, this paper conducted research about 3D virtual characters reconstructions through NeRF and illustrated the principals and functions of NeRF. Using two different datasets (Doll Photos Dataset and Real-Human Photos Datasets), this paper evaluated the NeRF model and provided researching advice for future research about dataset building and possible directions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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