Welcome to the Visual Anomaly and Novelty Detection 2026 Challenge, VAND 4th Edition workshop at CVPR 2026!

Our workshop challenge aims to showcase current progress in anomaly detection across different practical settings while addressing critical issues in the field. Building on the encouraging results from previous years — including the VAND 3.0 challenge — this edition sets its sights even higher, pushing the boundaries of robust and generalizable anomaly detection models for real-world use cases, for the first time including both industrial and retail logistics focused competitions. 

Challenge Objective and Categories

The challenge addresses critical industrial needs for reliable anomaly detection under varying conditions and with limited data. We aim to bridge academic research with industrial requirements to develop solutions directly applicable to manufacturing, retail logistics, and beyond. The challenge hosts two individual tracks:

• Industrial track: MVTec AD 2 

• Retail track: Kaputt 2

Participants can choose a single category or enter both in two separate submissions. These challenge categories aim to advance existing anomaly detection literature and increase its adaptation in real-world settings. We invite the global community of innovators, researchers, and technology enthusiasts: Engage with these challenges and contribute towards advancing anomaly detection technologies in real-world scenarios.

From April 1st to May 14th (AOE), 2026, the global community will showcase its ideas on how to solve these challenges in visual anomaly detection.

You will find a detailed description of the individual tracks below from March 25th, explaining the datasets used, the requirements for model design, the evaluation protocol, and points of contact, respectively. When in doubt about the participation and submission guidelines, please do not hesitate to reach out to us.

General Aspects

Important Dates

• Release of Detailed Track Descriptions: March 25th

• Challenge time: April 1st – May 14th (Anywhere on Earth)

• Submission Deadline: May 14th 23:59pm AOE

• Results Announcement: May 21st

• VAND4.0 workshop @CVPR26: June 3rd/4th
  Winners will have the chance to present their solution as a short video (5 min).
  Submission deadline for the video: May 28th (video presentation of the solution required to be eligible for prizes)
  
  

Model development

Participants are encouraged to explore and leverage any state-of-the-art anomaly detection, machine learning and vision(-language) models without limitations. Creativity and originality in model architecture and training methodology are strongly encouraged as long as they fulfil the category-specific requirements.

Datasets

For the Industrial Track, the MVTec AD 2 dataset will be used. Its design allows for evaluating models under real-world distribution shifts induced by changes in lighting conditions.

For the Retail Track, the Kaputt2 dataset will be used. The dataset is an extension of the Kaputt dataset released in 2025, illustrating scientific challenges for defect detection arising in retail logistics scenarios such as heavy pose and appearance variation. Kaputt2 will be released and made available at challenge start (April 1st).

Resources

• Anomalib GitHub

• Discord Channel #cvpr-challenge-vand4-0 

• Kaputt dataset

• MVTec Datasets

Participation Guidelines

This challenge is open to individuals, teams, and academic and corporate entities worldwide. Submission requirements, evaluation metrics, and additional eligibility criteria — in particular with respect to prize eligibility — will be detailed and shared upon the release of the detailed track descriptions on March 25th.

Prizes

Participate for a chance to win prizes!

There will be different prize categories rewarding not only high performance but also computational efficiency and innovative method design - stay tuned!

Challenge Organizers

Challenge Sponsors