October 29th, 2025 
Daniela Lopez de Luise The IEEE/CVF Winter Conference on Applications of Computer Vision 2026
Friday, March 6 – Tuesday, March 10, 2026 – Tucson, Arizona (USA)
Workshop Website: https://mivia.unisa.it/wastevision2026/
Contest Website: https://mivia.unisa.it/iwddcontest2026/
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=== Important dates ===
Method Submission Deadline: 10th December, 2025
Contest Paper Deadline: 15th December, 2025
Decision notification: December 23rd, 2025
Camera-ready: January 9th, 2026 (11:59 PM, PT)
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=== Contest ===
The Illegal Waste Dumping Detection (IWDD) contest is an international competition organized to encourage participants to develop advanced methods for real-time illegal waste dumping detection in videos captured by fixed CCTV cameras, runnable on smart cameras or embedded systems. Illegal dumping poses a major global issue, burdening cities with cleanup costs, harming ecosystems, and threatening public health. Variations in human behavior, waste types, and environmental factors reduce the effectiveness of conventional models. Limited availability of comprehensive, well-annotated video datasets. Most existing work relies on private datasets, hindering progress toward intelligent surveillance systems. We provide the participants with the MIVIA-IWDD dataset, which is a comprehensive collection of video clips specifically designed to train and evaluate action recognition models for detecting illegal waste disposal events. The dataset is completely balanced to ensure unbiased mod!
el training and robust evaluation. The dataset is perfectly balanced with equal representation: 200 positive samples (100 static + 100 dynamic) and 200 negative samples, ensuring unbiased training and fair evaluation metrics. Each positive video includes precise timestamp annotations marking the exact moment when illegal dumping occurs, enabling fine-grained temporal action localization and early detection training. The private test set includes both positive samples (videos containing illegal waste dumping events) and negative samples (videos with no dumping activity). The contest winner will be determined based on the highest F1-Score achieved on the test set, as it provides the most balanced evaluation of detection accuracy combining both precision and recall performance. However, to emphasize the applicability of these methods in real-time scenarios, we also compute additional metrics. To find the model with the best performance and the most efficient solution for real-!
time systems, we consider measures that evaluate both detectio!
n speed and computational efficiency. These metrics help identify methods that can operate effectively in resource-constrained surveillance environments while maintaining high detection accuracy. The detailed description can be read here: https://mivia.unisa.it/iwddcontest2026/
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=== Rules ===
– The deadline for the submission of the methods is 10th December, 2025. The submission must be done with an email in which the participants share (directly or with external links) the trained model, the code and the report.
– The participants can receive the training set and its annotations by sending an email to iwdd2026contest@gmail.com, in which they also communicate the name of the team.
– The participants can use these training samples and annotations for training and validating their methods, but they are also encouraged to use other external data for improving the performance of their models.
– The participants must submit their trained model and their evaluation code.
– The participants are strongly encouraged to submit a contest paper to WASTEVISION 2026, whose deadline is 15th December, 2025. To properly format their papers, authors must use the official WACV 2026 Author Kit Template, which contains all necessary LaTeX files, style sheets, and formatting guidelines required for submission. Authors can find complete instructions of how to format their papers in the workshop website https://mivia.unisa.it/wastevision2026/. Accepted papers will be included in the WACV 2026 Workshops Proceedings.
The detailed instructions can be read here: https://mivia.unisa.it/iwddcontest2026/
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Best regards,
The organizers
