Conference Information

QoMEX 2027: International Conference on Quality of Multimedia Experience

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QoMEX
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Submission Date:
2027-02-27 Due in 151 days
Notification Date:
2027-04-13
Conference Date:
2027-07-06
Location:
Shanghai, China
Years:
ICORE: B   Viewed: 21480   Tracked: 2   Attend: 0

Conference Partner Index (CP-I)

62.1 / 100
Ranked #536 of 5,687 conferences · Top 10%

#25 of 151 in Computer Graphics & Multimedia

Academic recognition (35%)
72
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
81
Community attention (10%)
25
Public record completeness (15%)
55

Inputs used: Listed as ICORE B · Editions on record: 19 · Researchers following it here: 2 · Researchers who opened this page in the past 24 months: 6

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-28

Call For Papers

QoMEX 2027 (International Conference on Quality of Multimedia Experience) is a ICORE B conference held in Shanghai, China on 2027-07-06. The paper submission deadline is 2027-02-27. Acceptance notifications are sent on 2027-04-13.

Topics of interest The QoMEX 2027 Organizing Committee solicits original contributions including, but not limited to, the following topics. Quality assessment and QoE modeling Multimedia Quality of Experience and User Experience Perceptual quality assessment for image, video, audio, and speech Quality assessment of 3D, volumetric, immersive, and XR media Multimodal and multisensory quality assessment Subjective assessment methodologies and user studies Objective, no-reference, and perceptual quality models QoE prediction, personalization, and adaptation Data-driven, learning-based, and hybrid QoE models Perceptual, semantic, and aesthetic quality Experience-aware multimedia systems Generative AI and intelligent media Quality of AI-generated content and synthetic media Perceptual and semantic quality of generative models Evaluation of generated image, video, audio, 3D, and multimodal content Foundation, language, and vision-language models for multimedia quality and QoE Human evaluation of generative and interactive AI systems Authenticity, trustworthiness, reliability, and provenance Hallucination, consistency, and perceptual artifacts Human-AI interaction and co-adaptation AI agents and intelligent systems for QoE-aware interaction Machine-oriented and semantic multimedia quality Immersive, 3D, and multimodal experiences Virtual, augmented, mixed, and extended reality Spatial computing and immersive communication 3D and 4D media, volumetric video, digital humans, neural representations, and novel scene representations Telepresence and remote immersive experiences Multimodal and multisensory experiences Visual, auditory, haptic, and cross-modal perception Presence, immersion, embodiment, and cybersickness Quality and experience of interactive and embodied media Networked media and experience-aware systems QoE-aware multimedia streaming and communication Adaptive media delivery and resource allocation QoE management in communication networks and systems Cloud, edge, and distributed media systems QoE in 5G-Advanced, 6G, and next-generation networks Intelligent networking and AI-assisted multimedia delivery Media compression, coding, and transmission from a QoE perspective Low-latency and interactive multimedia systems Energy-efficient and sustainable multimedia delivery Cross-layer and end-to-end QoE optimization Human factors, UX, and inclusive experiences Human factors in multimedia experiences Cognitive, emotional, behavioral, and attentional factors Human-computer interaction and novel interaction paradigms Quality of Life, well-being, and societal aspects of QoE Accessibility, diversity, and inclusive experience design Personalized and context-aware user experiences Ethics, privacy, consent, fairness, and explainability QoE for gaming, education, healthcare, culture, entertainment, and other applications User trust and acceptance of AI-mediated experiences Open science, datasets, benchmarks, and evaluation Datasets and benchmarks for multimedia quality and QoE Evaluation methodologies and protocols Reproducibility, replicability, and transparency Open-source tools and research infrastructure Crowdsourcing and large-scale subjective assessment Multimodal data collection and annotation Human-AI collaborative evaluation protocols Generalization, robustness, and cross-dataset evaluation Benchmarking emerging multimedia and intelligent systems Innovative approaches and emerging directions QoMEX 2027 also welcomes contributions that challenge established assumptions or introduce new paradigms, interdisciplinary perspectives, emerging applications, and unconventional methodologies for understanding multimedia quality and human experience.
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