2026 19th International Conference on Machine Vision (ICMV 2026)
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About this event
2026 19th International Conference on Machine Vision (ICMV 2026)
Dates: October 15–18, 2026
Venue: Budapest, Hungary
Organized by: University of Stuttgart, University of Barcelona, The Federal Research Center "Computer Science and Control" of the RAS, with support from Aberystwyth University, Skolkovo Institute of Science and Technology, and other global institutions.
About ICMV 2026
The 19th International Conference on Machine Vision (ICMV 2026) is a premier global platform for researchers, academics, and industry professionals to explore cutting-edge advancements in machine vision. Since its inception in 2007, ICMV has grown into a leading conference, fostering interdisciplinary collaboration and innovation. Building on the success of previous editions in Paris (2025), Edinburgh (2024), and Rome (2022), ICMV 2026 will emphasize machine vision as a catalyst for digital transformation.
Conference Highlights
- Keynote speeches and invited talks from renowned experts
- Oral and poster presentations of original research
- Special sessions on emerging technologies and applications
- Networking opportunities with global academia and industry leaders
- Publication opportunities through SPIE and indexed proceedings
Key Focus Areas
ICMV 2026 will address critical themes in machine vision, including:
- Theoretical advancements and novel algorithms in image processing and computer vision
- Industrial applications such as automation, quality inspection, and robotics
- Medical diagnostics and healthcare imaging technologies
- Mobile and wireless device-enabled integrative technologies
Venue & Location
Budapest, Hungary, renowned for its historic architecture, cultural vibrancy, and strategic location in Europe, will host ICMV 2026. The city offers a blend of academic ambiance and tourist attractions, making it an ideal setting for both professional engagement and leisure.
Organizing Institutions
- University of Stuttgart
- University of Barcelona
- The Federal Research Center "Computer Science and Control" of the RAS
- Aberystwyth University
- Skolkovo Institute of Science and Technology
- Ecole Nationale Supérieure des Mines de Saint-Etienne
- University of Electronic Science and Technology of China
- Sfax University
Publication & Indexing Partners
Accepted and presented papers will be published by SPIE and included in the SPIE Digital Library. Proceedings will be submitted for indexing in:
- Web of Science Conference Proceedings Citation Index-Science
- Scopus
- Ei Compendex
Call to Action
Researchers and professionals are encouraged to submit high-quality, original research papers covering all aspects of machine vision. Participation offers unparalleled opportunities for collaboration, knowledge exchange, and contributing to the future of the field.
For more information, visit the official website: https://www.icmv.org/
Data sheet
2026 19th International Conference on Machine Vision (ICMV 2026) – Event Attendee & Buyer Profile Analysis
Event date: October 15–18, 2026
Location: Budapest, Hungary
Event status: Upcoming
Research date: June 29, 2026
Event Overview
| Event Name | 2026 19th International Conference on Machine Vision (ICMV 2026) |
| Event Date | October 15–18, 2026 |
| Event Status | Upcoming |
| Venue | Specific venue not publicly confirmed in the official website text reviewed. |
| City | Budapest |
| State / Region | Budapest |
| Country | Hungary |
| Organizer | University of Stuttgart; University of Barcelona; The Federal Research Center "Computer Science and Control" of the RAS. Official website also states support from Aberystwyth University, Skolkovo Institute of Science and Technology, Ecole Nationale Supérieure des Mines de Saint-Etienne, University of Electronic Science and Technology of China, and Sfax University. |
| Official Event Website | www.icmv.org |
| Event Type | International academic and industry conference |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Industrial Engineering |
| Audience Reach | Global / international research and applied technology audience |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for numeric attendance; high for event date, city, country, organizer group, and conference theme based on the official website. |
| Main Purpose of Event | To present novel advances in machine vision, publish peer-reviewed research, connect academic and industry experts, and support collaboration around image processing, computer vision, automation, diagnostics, robotics, and digital transformation applications. |
About the Event
ICMV 2026 is the 19th edition of the International Conference on Machine Vision, scheduled for October 15–18, 2026 in Budapest, Hungary. According to the official event website, the conference serves as a leading international platform for researchers, academics, and industry professionals to present advances in machine vision, image processing, computer vision algorithms, and practical applications across automation, medical diagnostics, robotics, and mobile or wireless-enabled systems.
From a business development standpoint, ICMV is most relevant for organizations selling imaging components, AI/computer vision software, industrial automation systems, robotics solutions, edge computing, sensors, research tools, laboratory equipment, and technical services to universities, research institutes, advanced engineering groups, and innovation-led product teams. It is especially useful for lead generation where the target market includes R&D decision-makers, faculty labs, research centers, technical program leaders, and machine vision practitioners rather than broad general-trade attendees.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Academic researchers and principal investigators | Universities, engineering faculties, computer vision labs | Influence lab equipment, software, compute, imaging hardware, and research collaboration purchases | High relevance for scientific instruments, cameras, AI tooling, sensors, and publication-support services |
| Research institute scientists and lab managers | National research centers, applied sciences institutes, public R&D organizations | Evaluate technical platforms, imaging systems, datasets, software stacks, and collaborative projects | Strong relevance for grant-funded procurement and pilot deployments |
| Industrial R&D and innovation teams | Automation firms, robotics teams, smart manufacturing groups, applied AI units | Assess emerging algorithms, inspect technical maturity, and identify partnership opportunities | Relevant for proof-of-concept selling, co-development, and OEM/integration discussions |
| Computer vision software developers and data scientists | AI labs, software vendors, R&D engineering groups | Recommend model-development tools, cloud resources, annotation platforms, and GPU infrastructure | Useful for software trials, developer tooling, and technical product adoption |
| Industrial automation and quality inspection leaders | Factories, manufacturing engineering teams, inspection solution groups | Specify machine vision systems for defect detection, process control, and robotics guidance | High relevance for cameras, optics, software, robotics, and edge AI suppliers |
| Medical imaging and diagnostics researchers | Hospitals, medical research units, biomedical engineering departments | Influence adoption of vision algorithms, imaging software, and validation tools | Relevant for medical AI, imaging analytics, and compliance-enabled software vendors |
| Conference speakers, session chairs, and committee members | Senior academics, institute leaders, technical experts | High influence over partnerships, visibility, and institutional vendor introductions | Priority for relationship-led outreach and strategic collaborations |
| Graduate researchers and doctoral candidates | PhD programs, university labs, joint research initiatives | Lower direct purchasing authority but strong product evangelism and technical evaluation role | Useful for future pipeline, product testing, and adoption influence inside labs |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Budapest | Local academics, research labs, technology faculty, regional innovation groups | Medium | Host-city participation is likely, but no local attendee breakdown is publicly confirmed. |
| Hungary | National universities, technical institutes, engineering researchers, applied AI groups | Medium | National reach is likely due to the conference’s international positioning and Budapest location. |
| Central and Eastern Europe | Regional academic and technical attendees from nearby European research hubs | High | Budapest is accessible for European conference travel and likely attractive to regional participants. |
| Western Europe | Researchers and supporting institutions from Germany, Spain, France, UK, and broader Europe | High | Official organizers and supporters include institutions from Germany, Spain, France, and the UK. |
| Asia | Researchers from China and other Asian institutions engaged in computer vision research | Medium to High | Official supporting institutions include University of Electronic Science and Technology of China and Skolkovo Institute of Science and Technology. |
| Global | International academics and industry professionals | High | The official site explicitly positions ICMV as an international conference with global institutional participation. |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The official website repeatedly describes ICMV as an international conference and lists organizer/supporting institutions across multiple countries and prior editions in several European cities. |
| European | Secondary practical reach | Budapest location and the concentration of European organizing institutions suggest especially strong European participation. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| University of Stuttgart | University / organizer | Officially named organizer; relevant for research collaboration, imaging systems, compute, lab software, and machine vision tools. | uni-stuttgart.de | Professor, Principal Investigator, Research Group Leader, Lab Manager, Procurement Officer | Confirmed Current-Year Participant |
| University of Barcelona | University / organizer | Officially named organizer with likely faculty and research network influence in machine vision and applied AI. | ub.edu | Professor, Director Research Center, Principal Investigator, Technical Program Lead | Confirmed Current-Year Participant |
| Federal Research Center "Computer Science and Control" of the RAS | Public research institute / organizer | Official organizer relevant for advanced computer vision, automation, algorithmic research, and institutional procurement. | frccsc.ru | Institute Director, Laboratory Head, Senior Researcher, Research Procurement Officer | Confirmed Current-Year Participant |
| Aberystwyth University | University / supporting institution | Officially cited as supporting institution; relevant for academic collaboration and machine vision research procurement. | aber.ac.uk | Faculty Lead, Professor, Lab Manager, Research Operations Manager | Confirmed Current-Year Participant |
| Skolkovo Institute of Science and Technology | University / technology institute | Official supporting institution with strong relevance to AI, robotics, and technical innovation partnerships. | skoltech.ru | Research Center Director, AI Lab Lead, Program Manager, Innovation Partnerships Lead | Confirmed Current-Year Participant |
| Ecole Nationale Supérieure des Mines de Saint-Etienne | Engineering school / supporting institution | Official supporting institution relevant for applied machine vision, industrial engineering, and automation research. | emse.fr | Professor, Industrial Research Lead, Lab Manager, Applied Research Director | Confirmed Current-Year Participant |
| University of Electronic Science and Technology of China | University / supporting institution | Official support organization relevant for imaging, electronics, sensing, and computer vision R&D. | uestc.edu.cn | Dean, Research Professor, Laboratory Director, Technical Procurement Lead | Confirmed Current-Year Participant |
| Sfax University | University / supporting institution | Official supporting institution with likely faculty and research attendance in machine vision-related domains. | usf.tn | Professor, Department Head, Research Coordinator, Lab Buyer | Confirmed Current-Year Participant |
| SPIE | Professional society / publication partner | Official publication channel for accepted and presented papers; relevant for sponsorships, visibility, and technical audience access. | spie.org | Conference Manager, Partnerships Manager, Publications Director, Sponsorship Manager | Confirmed Current-Year Participant |
| ICMV 2025 Paris participant base | Historical conference community | The official website shows continuity of prior editions and published proceedings, indicating an established recurring audience. | icmv.org | Authors, Speakers, Research Leads, Lab Managers | Prior-Year Participation Evidence |
Prior-year participation evidence. Not a confirmed attendee list for the current edition.
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Professor / Principal Investigator | Research / Academic | Senior | Often controls research direction, grants, equipment recommendations, and external partnerships. |
| 2 | Laboratory Director / Lab Manager | Research Operations | Manager / Director | Directly involved in technical specification, vendor evaluation, and operational adoption. |
| 3 | Research Scientist / Senior Researcher | R&D | Mid-Senior | High technical influence over tool selection, testing, and proof-of-concept work. |
| 4 | Computer Vision Engineer | Engineering / AI | Mid-Level | Technical end user for software, models, hardware integration, and deployment tools. |
| 5 | Director of Research | R&D / Innovation | Director | Owns portfolio priorities, collaborative projects, and budget framing for new technology adoption. |
| 6 | AI / Machine Learning Lead | AI / Data Science | Manager / Director | Relevant where machine vision intersects with model development, data pipelines, and deployment. |
| 7 | Robotics Program Manager | Engineering / Program Management | Manager | Important for application-driven vision procurement in automation and robotic guidance. |
| 8 | Technical Procurement Officer | Procurement / Administration | Manager | Relevant in universities and institutes where procurement rules govern final purchasing. |
| 9 | Partnerships Director / Industry Liaison | Partnerships / External Relations | Director | Useful for sponsorships, co-research, visibility packages, and institutional introductions. |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Research | Directly aligned with conference-led scientific and technical research participation. | Research labs, institute buyers, technical program leaders |
| 2 | Higher Education | Universities and academic departments are central attendee groups. | Faculty labs, engineering schools, AI centers |
| 3 | Information Technology & Services | Relevant to enterprise and applied technology groups using computer vision. | Applied AI tools, software platforms, integration services |
| 4 | Computer Software | Machine vision development frequently depends on software frameworks and deployment tools. | Modeling, analytics, labeling, MLOps, CV applications |
| 5 | Industrial Automation | Official focus areas include industrial automation and quality inspection use cases. | Factory vision systems, robotics, inspection workflows |
| 6 | Mechanical or Industrial Engineering | Strong fit for engineering-led applications of machine vision in systems and production settings. | Applied engineering research, manufacturing innovation |
| 7 | Electrical/Electronic Manufacturing | Vision systems rely on sensors, imaging hardware, and embedded electronics. | Camera modules, edge devices, embedded vision components |
| 8 | Computer Hardware | Relevant for GPUs, edge processors, imaging platforms, and compute infrastructure. | High-performance compute, edge AI, hardware acceleration |
| 9 | Medical Devices | Official focus areas include medical diagnostics applications. | Imaging diagnostics, vision-assisted analysis, validation tools |
| 10 | Biotechnology | Relevant where vision supports scientific imaging and analytical workflows. | Lab imaging, analysis automation, research instrumentation |
| 11 | Government Administration | Relevant for publicly funded institutes and national research organizations. | Grant-backed research procurement and public R&D initiatives |
| 12 | Aviation & Aerospace | Machine vision is relevant in inspection, autonomy, and sensing-intensive research. | Inspection, autonomy, defect detection, robotics imaging |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Not confirmed | Official website text reviewed | No attendance number was published in the provided official content. |
| Exhibitor count | Not publicly confirmed | Not confirmed | Official website text reviewed | This appears to be a conference-first format rather than a trade exhibition-focused event. |
| Buyer count | Not publicly confirmed | Not confirmed | Official website text reviewed | No formal hosted buyer or procurement count disclosed. |
| Speaker count | Not publicly confirmed in the reviewed homepage text | Not confirmed | Official website text reviewed | Keynote and invited speaker sections exist, but no count was present in the supplied content. |
| Sponsor count | Not publicly confirmed | Not confirmed | Official website text reviewed | The website states sponsor opportunities are open, but no sponsor roster was included in the supplied text. |
| Historical attendance | Historical attendance figure not publicly confirmed in the provided official content | Historical data unavailable | Official website history and proceedings references | Prior-year locations and proceedings are listed, but audience size is not disclosed. |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Machine vision algorithms | Advanced model performance, new methods, reproducible results | Technical demos, benchmarking, research collaboration proposals | Computer vision software, AI frameworks, developer tools |
| Image processing | Higher accuracy, preprocessing efficiency, robust analytical pipelines | Workshop engagement, pilot tests, API evaluations | Image analytics platforms, annotation tools, optimization software |
| Industrial automation | Inspection, defect detection, robotic guidance, process control | Application-led case studies and system integration conversations | Industrial cameras, optics, edge AI, robotics vision systems |
| Quality inspection | Reliable visual QA and automated anomaly detection | POC offers tied to defect reduction and throughput gains | Inspection software, lighting systems, machine vision hardware |
| Medical diagnostics | Imaging analysis, classification, decision support | Research trials, validation partnerships, clinical AI discussions | Medical imaging AI, analytics, visualization tools |
| Robotics | Perception, motion guidance, environment understanding | Joint development and technical architecture meetings | Vision sensors, embedded AI, robotics software stacks |
| Mobile and wireless-enabled vision technologies | Edge deployment, lightweight inference, remote sensing use cases | Prototype discussion, low-latency deployment demos | Edge computing, wireless imaging, mobile AI solutions |
| Publication and academic visibility | Recognition, peer review, dissemination, indexing | Sponsorship, publication support, partnership branding | Conference sponsorships, academic outreach services, publishing support |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | High | Strong fit for suppliers targeting research, machine vision, AI, robotics, inspection, and scientific computing buyers. |
| Decision-maker availability | Medium | Senior technical influencers are likely present, but some final purchases may still route through institutional procurement or grant processes. |
| Data collection potential | Medium | Conference websites often provide committees, speakers, and authors, but not always direct buyer-style attendee lists. |
| Apollo targeting potential | High | Research, higher education, software, automation, and hardware sectors are highly targetable in Apollo using title and department filters. |
| Geographic targeting potential | High | Useful for Europe-first outreach with global expansion to research-active institutions. |
| Best outreach approach | High | Use technical credibility messaging, research collaboration angles, demo offers, and application-specific use cases rather than generic sales copy. |
| Overall lead quality | High | Particularly strong for niche B2B and technical sellers with offerings tied to computer vision and research environments. |
| Best use case | High | Ideal for targeted lead generation, academic/industrial partnership outreach, and speaker-author-account-based prospecting. |
| Limitations / risks | Medium | Not ideal for mass attendee list building unless official author, speaker, or committee data is expanded. Numeric attendance and buyer counts are not publicly confirmed in the reviewed source. |
B2B attendee list building suitability: Moderate. Best when built from official committees, speakers, authors, and organizer/supporting institution networks rather than expecting a classic trade show buyer directory.
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Research; Higher Education; Information Technology & Services; Computer Software; Industrial Automation; Mechanical or Industrial Engineering; Electrical/Electronic Manufacturing; Computer Hardware; Medical Devices; Government Administration | Capture the institutions and applied-technology buyers most aligned to ICMV themes. |
| Departments | Research; Engineering; Information Technology; Operations; Procurement; Education | Find technical evaluators plus administrative buyers. |
| Seniority | Director; VP; CXO; Manager; Owner; Partner; Senior; Head | Prioritize decision-makers and senior technical influencers. |
| Job titles | Professor, Principal Investigator, Research Scientist, Director of Research, Laboratory Director, Lab Manager, Computer Vision Engineer, AI Lead, Machine Learning Lead, Robotics Engineer, Technical Program Manager, Procurement Officer, Partnerships Director | Build a focused list of both buyers and high-influence technical users. |
| Geography | Hungary; Germany; Spain; France; United Kingdom; China; broader Europe | Mirror organizer/supporter footprint and likely attendee corridors. |
| Employee size | 51–200; 201–500; 501–1,000; 1,001–5,000; 5,001+ | Useful for universities, institutes, and mature engineering organizations. |
| Keywords | machine vision, computer vision, image processing, AI, robotics, industrial inspection, medical imaging, deep learning, edge AI, visual analytics | Narrow to directly relevant organizational and contact profiles. |
| Technologies | Use if available: computer vision stack, AI/ML platforms, GPU/cloud infrastructure, robotics platforms | Helps find accounts already investing in machine vision capability. |
| Revenue range | Optional; use broader bands due university and public institute mix | Avoid over-filtering research organizations that may not disclose standard corporate revenue signals. |
| Company type | Educational institutions, research institutes, public-sector research organizations, engineering firms, software companies | Align with likely attendee and sponsor ecosystem. |
Suggested Apollo Search Logic: ("machine vision" OR "computer vision" OR "image processing" OR "medical imaging" OR robotics OR "industrial inspection") AND (Professor OR "Principal Investigator" OR "Research Scientist" OR "Director of Research" OR "Lab Manager" OR "Computer Vision Engineer" OR "AI Lead") within Research, Higher Education, Industrial Automation, Computer Software, and Information Technology & Services industries.
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| ICMV 2026 Official Website | Official event website | Event name, edition number, dates, city, country, event positioning, organizer institutions, supporting institutions, conference themes, publication route, and prior-year edition references | High |
| ICMV 2026 Homepage welcome text | Official event copy | Confirmed wording that ICMV is a leading international conference for machine vision and that Budapest, Hungary is the host location for October 15–18, 2026 | High |
| ICMV History / Proceedings references on official site | Official historical listing | Continuity of prior editions from 2007–2025 and evidence of published proceedings for prior years | High for historical continuity; does not confirm 2026 attendee numbers |
| Research limitation note | Methodology note | No current-year attendee count, speaker count, exhibitor count, specific venue, or official buyer list was present in the supplied official source text reviewed for this report. | High confidence limitation statement |
🎯 Selling to this event's audience? Get a free tailored buyer list
Tell us your work email and our AI instantly builds a buyer list matched to 2026 19th International Conference on Machine Vision (ICMV 2026) — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
🔒 Get my buyer details Free · ~20 seconds