| ---
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| license: other
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|
|
| task_categories:
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| - object-detection
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|
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| language:
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| - en
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|
|
| tags:
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| - computer-vision
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| - object-detection
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| - pascal-voc
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| - annotation-quality
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| - dataset-cleaning
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| - label-noise
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| - corruption-detection
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| - reproducibility
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|
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| pretty_name: VOC2012 Training-Free Cleaned Annotations
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|
|
| size_categories:
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| - 10K<n<20K
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|
|
| annotations_creators:
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| - expert-generated
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|
|
| source_datasets:
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| - extended
|
| ---
|
|
|
| # Cleaned VOC2012 Dataset
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|
|
| ## Overview
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|
|
| This repository provides a curated version of the PASCAL VOC2012 object detection dataset.
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|
|
| The dataset combines two independent cleaning stages:
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|
|
| 1. Hasty.ai quality-controlled annotations.
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| 2. Additional corrections based on training-free feature-space corruption detection as presented in:
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|
|
| **Analyzing Training-Free Corruption Detection for Object Detection Datasets**
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|
|
| The objective of this repository is not to provide a definitive error-free benchmark, but to provide a reproducible research artifact for studying annotation quality and corruption detection in object detection datasets.
|
|
|
| ---
|
|
|
| ## Dataset Structure
|
|
|
| ```
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| VOC2012/
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| ├── Annotations/
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| │ └── *.xml
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| │
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| ├── hasty_cleaned_annotations/
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| │ ├── combined/
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| │ ├── train/
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| │ ├── validation/
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| │ ├── test/
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| │ └── Clean_PASCAL_COCO_Format.json
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| │
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| ├── training_free_cleaned_annotations/
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| │ ├── annotations/
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| │ ├── image_examples/
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| │ │ ├── badly_located/
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| │ │ ├── mislabel/
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| │ │ └── others/
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| │ │
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| │ ├── correction_report.json
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| │ └── Cleaned_PASCAL_COCO_Format.json
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| ```
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|
|
| The `Annotations` directory contains the original PASCAL VOC2012 annotations.
|
|
|
| The `hasty_cleaned_annotations` directory contains the quality-controlled annotations provided by Hasty.ai.
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|
|
| The `training_free_cleaned_annotations` directory contains the corrections generated during this work, including correction reports and visual examples of modified annotations.
|
|
|
| ---
|
|
|
| ## Cleaning Methodology
|
|
|
| Potential annotation inconsistencies were identified using a training-free feature-space-based corruption detection pipeline.
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|
|
| The pipeline operates on individual object instances by extracting bounding-box crops and analyzing their similarity within a feature space generated by pretrained visual embedding models.
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|
|
| Detected annotations were manually inspected and categorized into:
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| - Mislabel: Incorrect semantic class assignment.
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| - Badly located: Bounding boxes that do not accurately enclose the object.
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| - Other: Remaining annotation inconsistencies.
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|
|
| The approach is effective at identifying semantic inconsistencies but remains less sensitive to positional errors. Therefore, despite the applied cleaning stages, remaining annotation errors may still exist.
|
|
|
| ---
|
|
|
| ## Dataset Statistics
|
|
|
| The Hasty.ai cleaned version contains:
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| - 17,119 images
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| - 43,294 annotated objects
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|
|
| During our additional inspection, 63 remaining annotation errors were identified and removed:
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| - 24 mislabels
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| - 15 badly located bounding boxes
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| - 24 other inconsistencies
|
|
|
| ---
|
|
|
| ## Intended Use
|
|
|
| This dataset is intended for:
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| - Research on dataset auditing.
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| - Evaluation of annotation corruption detection methods.
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| - Controlled experiments involving synthetic annotation noise.
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| - Reproducibility of the experiments presented in the associated publication.
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|
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| It should not be treated as a guaranteed ground-truth dataset.
|
|
|
| ---
|
|
|
| ## Citation
|
|
|
| If you use this dataset, please cite:
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|
|
| 1. The original PASCAL VOC publication.
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|
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| 2. The Hasty.ai PASCAL cleaning work.
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|
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| 3. The publication introducing the training-free cleaning procedure. [Link](https://arxiv.org/abs/2606.10666)
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|
|
| Sieberichs, C., Geerkens, S., Waschulzik, T., Viswanathan, R., and Braun, A.
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| Analyzing Training-Free Corruption Detection for Object Detection Datasets. DataCV 2026
|
|
|
| ---
|
|
|
| ## Acknowledgements
|
|
|
| This repository only provides additional annotation files, documentation, and corrections generated during the cleaning process. The images can be found at the original VOC (https://www.robots.ox.ac.uk/~vgg/projects/pascal/VOC/) and are not provided within this repository. |
