To this end, we propose a novel Adaptive Multi-scale Context Aggregation Network (MSCANet), in which a Multi-scale Context Aggregation module (MSCA) is designed to adaptively extract and aggregate the contextual information from different scales of the crowd.

However, most of the existing methods donвЂ™t fully utilize spatial context information, and it is difficult for them to count the congested crowd accurately. The papers cover topics such as: multimedia indexing multimedia mining multimedia abstraction and summarization multimedia annotation, tagging and recommendation multimodal analysis for retrieval applications semantic analysis of multimedia and contextual data multimedia fusion methods multimedia hyperlinking media content browsing and retrieval tools media representation and algorithms audio, image, video processing, coding and compression multimedia sensors and interaction modes multimedia privacy, security and content protection multimedia standards and related issues advances in multimedia networking and streaming multimedia databases, content delivery and transport wireless and mobile multimedia networking multi-camera and multi-view systems augmented and virtual reality, virtual environments real-time and interactive multimedia applications mobile multimedia applications multimedia web applications multimedia authoring and personalization interactive multimedia and interfaces sensor networks social and educational multimedia applications and emerging trends.Д¬rowd counting has achieved significant progress with deep convolutional neural networks. Of the 211 submitted regular papers, 40 papers were selected for oral presentation and 33 for poster presentation 16 special session papers were accepted as well as 2 papers for a demo presentation and 17 papers for participation at the Video Browser Showdown 2021. The two-volume set LNCS 125 constitutes the thoroughly refereed proceedings of the 27th International Conference on MultiMedia Modeling, MMM 2021, held in Prague, Czech Republic, in June2021.

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