VISION'26 @ CVPR 2026

Overview

Aims and Scope

The VISION workshop will provide a platform for the exchange of scholarly innovations and emerging practical challenges in Vision-based Industrial Inspection. Through a series of keynote talks, technical presentations, and challenge competitions, this workshop aims to (i) bring together researchers from the interdisciplinary research communities related to computer vision-based inspection; and (ii) connect researchers and industry practitioners to synergize recent research progress and current needs in industrial practice.

In 2026, VISION expands its scope to reflect the merger with the “DEgraded X-ray image Tomography, Enhancement, and Reconstruction” and “Intelligent Screening and Imaging For Detection and Exploitation via X-ray” workshops.

We explicitly welcome contributions across these three tracks, from traditional vision based methods to cross-modality methods and shared challenges in real-world inspection pipelines.

Topics include surface imaging, X-ray, CT, and volumetric reconstruction, 3D sensing modalities, computational imaging, imaging physics, multimodal cross-domain fusion, scene understanding for threat detection, datasets and benchmarking, and real-world deployment and applications.

Keynote Talks

Salman Khan

Computer Vision Department, MBZUAI

"Intelligent Security Screening X-ray"

Dan Cristian Dinca

Raspican Systems

TBD

Time	Topic
8:00 - 8:05	Chair's Opening Remarks
8:05 - 8:25	Keynote Talk I: Salman Khan — "Intelligent Security Screening X-ray"
8:25 - 8:45	Keynote Talk II: Dan Cristian Dinca — TBD
8:45 - 9:05	Keynote Talk III: TBD
9:05 - 9:35	flash talk (oral paper presentation, aim for 3 mins per paper)
9:35 - 10:15:	poster session & Coffee Break
10:15 - 10:35	Keynote Talk IV: TBD
10:35 - 10:55	Keynote Talk V: TBD
10:55 - 11:15	Keynote Talk VI: TBD
11:15 - 12:00:	Panel discussion

Call for Papers

Topics of Interest (not limited to)

From an industry point of view:

New developments and evolving practices across industries such as automotive, electronics, and construction, focusing on materials like glass, carbon fiber, metal, and plastic.
Advances in vision-based inspection technologies, the rise of foundation models, and the challenges these bring in terms of algorithm development (e.g., multi-modal data fusion, physics-informed learning)
Integration of automated screening in airports, borders, and logistics
Mitigating evolving threat types, such as miniaturized explosives, dismantled improvised explosive devices
Edge and real-time implementations for high-throughput inspection and screening
Adaptive triage systems to optimize Human–AI collaboration
Imaging-based non-destructive testing
Release of large-scale industrial inspection and screening datasets.

From an academic point of view:

Algorithms for Data and Annotation Limitations
Techniques to Overcome Real-world Data Challenges
Data-centric Tools and Methodologies
Robust, Explainable, and Accountable Machine Learning
Meta-Learning, Transfer Learning, and Domain Adaptation
Foundation Models in Industrial Inspection and Security Screening
Multi-Modality, Multi-Energy Data Fusion for Inspection and Screening
Context-aware, fine-grained, and part-based analysis of concealed or dismantled threats
One-class and open-set recognition for rare or unseen threats
Generative AI and diffusion models for synthetic X-ray and CT data augmentation
Spectral and hyperspectral X-ray imaging for material discrimination
Physics-informed deep learning for material and substance classification
Quantitative imaging for distinguishing organic, inorganic, and metallic substances

Submission Instructions

We invite research and industrial papers relevant to the workshop topics. Authors may choose between:

Regular papers: Full-length submissions eligible for the workshop proceedings (details will follow the CVPR 2026 workshop guidelines).
Extended abstracts: Short submissions that will not appear in the proceedings.

Tracks (new for 2026)

This year, we offer three submission tracks. Authors are encouraged to submit to the track that best matches their paper's focus:

VISION'26 General Track
DEXTER Track: DEgraded X-ray image Tomography, Enhancement, and Reconstruction
INSIDE-X Track: Intelligent Screening and Imaging for Detection and Exploitation via X-ray