Waterloo Urban Scene Dataset: An Annotation-Efficient Dataset for Urban Scene Classification with Minimal Supervision
Why this work is in the frame
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Bibliographic record
Abstract
High-definition (HD) urban scene mapping is crucial for urban applications and autonomous driving.However, achieving high performance in HD mapping requires large amounts of high-quality annotated data.While the SkyScape dataset is valuable, it is limited by its focus on lane markings in Germany.In this paper, we present the Waterloo Urban Scene Dataset, built upon the Waterloo Building Dataset, designed for minimal supervision deep learning.The dataset includes 907 well-annotated, 775 roughly annotated, and 23,172 intact patches (512 512 pixels, 0.12m/pixel resolution in RGB).Combined with the SkyScape dataset, it supports HD urban scene mapping with minimal supervision.Future work will focus on benchmarking and method development.
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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 | 0.001 | 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 | 0.000 |
| 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