We invite high-quality research papers and reports on best practices in the field of Computer Vision and Machine Learning that address the following (and related) issues:

1. The Human Body, Face, and Behaviour

• Action and Gesture Recognition

• Facial Expression and Emotion Detection 

• Posture Estimation and Anthropometric Measurement 

• Gait and Biomechanical Analysis 

• Behaviour Understanding and Social Interaction Modelling 

• Motion patterns linked to cognitive or affective states 

• Multimodal fusion with bio-signals (EMG, EEG, heart rate, respiration) 

2. Generative AI, Foundation Models, and Advanced Modelling

   • Motion Foundation Models (MFMs)

   • Motion-Language Models (MLMs) 

   • Motion diffusion models, transformers, and large-scale pretraining 

   • Digital human generation and avatar motion synthesis 

   • Synthetic data for training and bias mitigation 

   • Privacy-preserving data collection and anonymized motion 

   • First-person vision and egocentric behaviour understanding 

3. Systems, Tools, and Real-Time Architectures 

   • Edge AI and efficient mobile motion analysis

   • Lightweight and sparse multimodal systems 

   • Tools and frameworks for large-scale motion datasets 

   • Explainability, transparency, and fairness in motion systems 

   • Real-time motion tracking in complex environments 

4. Applications Across Domains 

   • Personalized rehabilitation and physiotherapy 

   • Sports performance analytics and virtual coaching 

   • Human-robot collaboration and predictive motion models 

   • Safety-critical applications (autonomous driving, robotics) 

   • Crowd behaviour, group dynamics, and public safety

   • Immersive media: avatars, XR interactions, digital humans 

   • Remote physiological monitoring and health assessment 

5. Sensing Modalities and Computational Challenges

   • Thermal, hyperspectral, and radar-based motion capture 

   • Fusion of cameras, IMUs, bio-signals, and environmental sensors

   • New motion datasets, benchmarks, and evaluation protocols 

   • Scalability and computational efficiency for large systems.

We encourage submissions that address theoretical advancements, practical challenges, and the ethical implications of these technologies, as well as interdisciplinary research that bridges AI, computer vision, and application-specific domains

Submission Information

Submissions should be made through the following LINK.

https://cmt3.research.microsoft.com/ICMEW2026/ 

The papers will have the following commonalities:

• Length: Papers must be no longer than 6 pages, including all text, figures, and references.

• Format: Workshop papers have the same format as regular papers. See the example paper under the General Information section below. However, they need not be double-blind.

• Review: Reviews will be handled directly by the Workshop organizers.

• Submission site: Papers must be submitted under the track for the appropriate Workshop. Submissions may be accompanied by up to 20 MB of supplemental material following the same guidelines as regular and special session papers.

• Presentation guarantee: As with accepted Regular and Special Session papers, accepted Workshop papers must be registered by the author deadline and presented at the conference; otherwise they will not be included in IEEE Xplore.

• A workshop paper is covered by a full-conference registration only.

For detailed instructions, please see https://2026.ieeeicme.org/author-information-and-submission-instructions/ 

Session Chairs (TBD)