A state-based game attention model for cloud gaming
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
One of the main promises of cloud gaming, an emerging and growing market in the gaming industry, is its lack of dependence on high-end hardware. To fulfill its goal of enabling anyone to play their favorite games whenever, wherever and on any device, it requires high bandwidth, which remains a major challenge. One solution is to model or predict the players' visual attention map and allocate bitrate accordingly, thereby reducing the bandwidth. The first step of this solution is to predict the players' visual attention maps, which is the objective of our work. In this paper, we demonstrate experimentally that the predicted visual attention maps can be further improved by incorporating game state. Furthermore, we propose a game attention model based on game states. To evaluate the model, we have prepared a 92 minute dataset of states of three games. The results indicate that incorporating game states into visual attention models improves the accuracy of the predicted attention maps by 17.4% on average.
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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 | 0.000 | 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 | 0.000 | 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