Real-time robust tracking with part-based and spatio-temporal context
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
Owing to the significant and excellent performance of correlation filter in the aspect of computation convenience, correlation filters based trackers have become increasingly popular in the visual object tracking community. However, complete or partial occlusion is one of the major factors that seriously impact the tracking performance in visual tracking. To address this issue, we propose a novel tracking algorithm that perfectly integrates the results from the global correlation and local correlation filters for estimating the more accurate position of target. Then, we introduce the occlusion detection mechanism to eliminate the occlusion impact on the final position of object. In addition, our proposed tracker employs the spatial geometric constraints among the global object and local patches of object for preserving the structure integration of object. For verifying our method, we conduct extensive qualitative and quantitative experiments on challenging benchmark image sequences.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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 it