Current Issue : October-December Volume : 2025 Issue Number : 4 Articles : 5 Articles
This study presents an exhaustive analysis of LGBTQIA+ audiovisual production available on the main streaming platforms in Spain, covering both Spanish and international content. Using a sample of 1490 works from ten video-on-demand services (Apple TV+, Disney+, Filmin, FlixOlé, Max, Movistar Plus+, Netflix, Prime Video, Rakuten, and SkyShowtime), this study examines how the offered catalogues are configured and structured in response to the commercial dynamics of the LGBTQIA+ production market. Using quantitative methodology, the research addresses the industrial production models, the agents involved and the characteristics of the most widely offered narrative genres and formats, highlighting distribution patterns and visibility in the catalogues. The findings include a marked international abundance, a reflection of the global market guidelines and the hegemony of narratives aimed at transnational audiences. National productions, although less numerous, are a significant contribution to the audiovisual landscape, incorporating cultural identities with an LGBTQIA+ representation that is more aligned with local realities. The central role of independent producers is observed in production models where international agreements are outlined as a key strategy. In addition, it highlights the prevalence of genres such as drama and comedy, together with that of the film format. The visibility and representation of sexual and gender diversity indicates a positive commercial response, although with considerable challenges....
As Taiwan is about to enter a super-elderly society (the elderly over 65 years old account for more than 20% of the total population), how to delay disability and dementia in the elderly has become an important issue. Increasing the use of toys and games for the elderly delays their disability. Therefore, we developed three 3D interactive games for the elderly using mixed-reality (MR) technology. The three games were designed for hand-eye coordination, including digital cognition, object shape recognition, and color recognition ability. The reaction time was recorded to analyze the elderly’s reaction ability when playing the games. The questionnaire survey results showed that more than 83% of the elderly were satisfied with the use of MR equipment. More than 87% of the elderly accepted the interactive mechanism of MR while more than 80% felt that the three games improved their reaction ability....
The video transformer model, a deep learning tool relying on the self-attention mechanism, is capable of efficiently capturing and processing spatiotemporal information in videos through effective spatiotemporal modeling, thereby enabling deep analysis and precise understanding of video content. It has become a focal point of academic attention. This paper first reviews the classic model architectures and notable achievements of the transformer in the domains of natural language processing (NLP) and image processing. It then explores performance enhancement strategies and video feature learning methods for the video transformer, considering 4 key dimensions: input module optimization, internal structure innovation, overall framework design, and hybrid model construction. Finally, it summarizes the latest advancements of the video transformer in cutting-edge application areas such as video classification, action recognition, video object detection, and video object segmentation. A comprehensive outlook on the future research trends and potential challenges of the video transformer is also provided as a reference for subsequent studies....
The rapid growth of information and communication technologies, in particular big data, artificial intelligence (AI), and the Internet of Things (IoT), has made it possible to make smart cities a tangible reality. In this context, real-time video surveillance plays a crucial role in improving public safety. This article presents a systematic review of studies focused on the detection of acts of aggression and crime in these cities. By studying 100 indexed scientific articles, dating from 2018 to 2024, we examine the most recent methods and techniques, with an emphasis on the use of machine learning and deep learning for the processing of real-time video streams. The works examined cover several technological axes such as convolutional neural networks (CNNs), fog computing, and integrated IoT systems while also addressing issues such as the challenges related to the detection of anomalies, frequently affected by their contextual and uncertain nature. Finally, this article offers suggestions to guide future research, with the aim of improving the accuracy and efficiency of intelligent monitoring systems....
Multi-modal large language models (MLLMs) models have made significant progress in video understanding over the past few years. However, processing long video inputs remains a major challenge due to high memory and computational costs. This makes it difficult for current models to achieve both strong performance and high efficiency in long video understanding. To address this challenge, we propose Video-XL-2, a novel MLLM that delivers superior cost-effectiveness for long-video understanding based on task-aware KV sparsification. The proposed framework operates with two key steps: chunk-based pre-filling and bi-level key-value decoding. Chunk-based pre-filling divides the visual token sequence into chunks, applying full attention within each chunk and sparse attention across chunks. This significantly reduces computational and memory overhead. During decoding, bi-level key-value decoding selectively reloads either dense or sparse key-values for each chunk based on its relevance to the task. This approach further improves memory efficiency and enhances the model’s ability to capture fine-grained information. Video-XL-2 achieves state-of-the-art performance on various long video understanding benchmarks, outperforming existing open-source lightweight models. It also demonstrates exceptional efficiency, capable of processing over 10,000 frames on a single NVIDIA A100 (80GB) GPU and thousands of frames in just a few seconds. Video-XL-2 has been made publicly available at this repo....
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