CBMI — Content-Based Multimedia Indexing

CBMI aims at bringing together the various communities involved in all aspects of content-based multimedia indexing for retrieval, browsing, management, visualization and analytics. Authors are encouraged to submit previously unpublished research papers in the broad field of content-based multimedia indexing and applications. We wish to highlight significant contributions addressing the main problem of search and retrieval but also the related and equally important issues of multimedia content management, user interaction, large-scale search, learning in retrieval, social media indexing and retrieval.

Topics: Audio and visual and multimedia indexing, Multimodal and cross-modal indexing, Deep learning for multimedia analysis and indexing, Audio (speech, music, etc) and visual content analysis and understanding, Identification and tracking of semantic regions and events, Social media analysis, Metadata generation, coding and transformation, Activity recognition and event-based multimedia indexing, spiking neural networks, Multimedia information retrieval (image, audio, video, text), Mobile media retrieval, Event-based media retrieval, Affective/emotional interaction or interfaces for multimedia retrieval, Multimedia data mining and analytics, Multimedia retrieval for multimodal analytics and visualisation, Multimedia recommendation, Multimedia verification (e.g., multimodal fact checking, deep fake analysis), Large scale multimedia database management, Summarization, browsing and organization of multimedia content, Evaluation and benchmarking of multimedia retrieval systems, User interaction and relevance feedback, Multimedia interfaces, presentation and visualization tools, Personalization and content adaptation, Virtual, augmented and mixed reality interfaces for multimedia search, Applications of multimedia indexing and retrieval