Alexandria Engineering Journal is cited in the Engineering Information Services (EIS) and the Chemical Abstracts (CA). The papers published in Alexandria Engineering Journal are grouped into five sections, according to the following classification: • Electrical Engineering, Computer Science and Nuclear Engineering.

2023年5月22日 · Abstract: This work introduces Video Diffusion Transformer (VDT), which pioneers the use of transformers in diffusion-based video generation. It features transformer blocks with modularized temporal and spatial attention modules to leverage the rich spatial-temporal representation inherited in transformers.

2025年2月27日 · Leveraging the advancement of the state understanding of Visual Language Model (VLM), incorporating with diffusion Transformer-based action generation, our VDT-Auto parses the environment geometrically and contextually for the conditioning of …

2024年2月28日 · 提出统一的时空掩码建模机制，使 VDT 能够处理多种视频生成任务，实现了技术的广泛应用。VDT 灵活的条件信息处理方式，如简单的 token 空间拼接，有效地统一了不同长度和模态的信息。

Alexandria Engineering Journal is an international journal devoted to publishing high quality papers in the field of engineering and applied science. Alexandria Engineering Journal is cited …

2024年2月25日 · 研究团队提出了 基于 Transformer 的 Video 统一生成框架 - Video Diffusion Transformer (VDT)，并对采用 Transformer 架构的原因给出了详细的解释。 与主要为图像设计的 U-Net 不同，Transformer 能够借助其强大的 token 化和 注意力机制，捕捉长期或不规则的时间依赖性，从而更好地处理时间维度。 只有当模型学习（或记忆）了世界知识（例如空间时间关系和物理法则）时，才能生成与现实世界相符的视频。 因此，模型的容量成为视频扩散的一个关键 …

This work introduces Video Diffusion Transformer (VDT), which pioneers the use of transformers in diffusion-based video generation, and proposes a unified spatial-temporal mask modeling mechanism, seamlessly integrated with the model, to cater to diverse video generation scenarios.

2024年8月19日 · Alexandria Engineering Journal《亚历山大工程学报》作为一本国际知名的EI和SCI双检索期刊，在工程学科领域具有较高的学术影响力和广泛的认可度。 其发文量较大，对国人友好，且审稿周期相对较短，是广大科研工作者发表高质量学术论文的优选期刊之一。 对于希望在该领域展示研究成果、提升学术影响力的学者来说，Alexandria Engineering Journal无疑是一个值得推荐的投稿选择。 期刊基本信息. 期刊影响力与排名. 影响因子：根据最新数据，Alexandria …

We first describe the vehicular digital twin network architecture in detail and then investigate some VDT-related applications. After that, we discuss the security and privacy issues in VDT. Finally, we put forward several potential countermeasures and open research issues for VDT from the perspective of security and privacy.

This work introduces Video Diffusion Transformer (VDT), which pioneers the use of transformers in diffusion-based video generation. It features transformer blocks with modularized temporal and spatial attention modules, allowing separate optimization of each component and leveraging the rich spatial-temporal representation inherited from ...