VAND 4.0 - Visual Anomaly & Novelty Detection Workshop CVPR'26

VAND brings together cutting-edge research on detecting what doesn’t belong in visual data—spanning anomaly, novelty, and out-of-distribution detection. Building on three successful editions, VAND 4.0 unites supervised, semi-, and unsupervised approaches, including few-, one-, and zero-shot learning, with a strong focus on real-world impact.

Join us for  peer-reviewed papers, dataset-driven challenges, and invited talks on anomaly detection. This workshop brings together researchers from both industry and academia to present and discuss recent advances, opportunities, and open challenges in visual anomaly detection.

Our call for papers for VAND 2026 includes the following topics:

• Anomaly detection, novelty detection, and out-of-distribution detection in images and videos.

• Relevant learning paradigms including unsupervised, few-shot and active learning.

• Dataset challenges including highly imbalanced data, noisy/incomplete labels, data sampling, applications spanning vision-based industrial inspection, predictive maintenance of complex machines.

• Adjacent domains such as in-field inspection and medical diagnosis.

• Theoretical contributions that address challenges unique to anomaly detection and novelty detection.

Our workshop will only be accepting full papers.

Full paper submissions to the workshop must be of 8 page papers, with unlimited space for references and supplementary materials, following the CVPR 2026 style and formatting guidelines. The review process is double-blind and there is no rebuttal. Submissions must not have been previously published in a substantially similar form. Accepted papers will be invited for either spotlight talks or poster presentations. Accepted papers will be published in conjunction with CVPR 2026 proceedings. 

Submission Portal:  OpenReview-Submission-Portal

Important Dates: All deadlines are end-of-day in the Pacific time zone

• Submission deadline: Feb 26, 2026 (Anywhere on Earth) DEADLINE EXTENDED: Mar 02, 2026 (Anywhere on Earth) 

• Author notification: Mar 20, 2026 (Anywhere on Earth) 

• Camera-ready deadline: Apr 08, 2026 (Anywhere on Earth) 

• Workshop: June 3rd or 4th, 2026

Please check the Call for Papers page for more details.

We retain two complementary tracks that map to pressing industrial needs: 

1. Category 1 — Adapt & Detect: Robust & Efficient Anomaly Segmentation

2. Category 2 — VLM Anomaly Challenge: Few-Shot Logical & Structural Detection.

Both tracks are designed to (i) stress-test under realistic conditions (domain shift, limited supervision, resource limits) & (ii) incentivize accuracy, robustness, and efficiency.

Please check the Challenge page for more details.