Over the last decade, the use of Deep Learning in many applications produced results that are comparable to and in some cases surpassing human expert performance. The application domains include diagnosing diseases, finance, agriculture, search engines, robot vision, and many others. In this paper, we are proposing an architecture that utilizes image/video captioning methods and Natural Language Processing systems to generate a title and a concise abstract for a video. Such a system can potentially be utilized in many application domains, including, the cinema industry, video search engines, security surveillance, video databases/warehouses, data centers, and others. The proposed system functions and operates as followed: it reads a video; representative image frames are identified and selected; the image frames are captioned; NLP is applied to all generated captions together with text summarization; and finally, a title and an abstract are generated for the video. All functions are performed automatically. Preliminary results are provided in this paper using publicly available datasets. This paper is not concerned about the efficiency of the system at the execution time. We hope to be able to address execution efficiency issues in our subsequent publications.
ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP
Khalifa University（卡利法大学）；University of Western Australia（西澳大学）；The Chinese University of Hong Kong（香港中文大学）；University of Melbourne（墨尔本大学）；University of Central Florida（佛罗里达中央大学）
Clinical-Prior Guided Multi-Modal Learning with Latent Attention Pooling for Gait-Based Scoliosis Screening
Orthopaedic Centre, The University of Hong Kong - Shenzhen Hospital, Shenzhen, China（香港大学深圳医院骨科中心）；Translational Medicine Centre, The University of Hong Kong - Shenzhen Hospital, China（香港大学深圳医院转化医学中心）；Department of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China（香港大学李嘉成医学院骨科及创伤外科学院）；Huawei, China（华为）
Learning Transferable Spatiotemporal Representations from Natural Script Knowledge
Tsinghua University（清华大学）；The University of Hong Kong（香港大学）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））；Applied Research Center (ARC), Tencent PCG（腾讯平台与内容事业群应用研究中心）
UniEmoX: Cross-modal Semantic-Guided Large-Scale Pretraining for Universal Scene Emotion Perception
School of Artificial Intelligence, Anhui University（安徽大学人工智能学院）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥国家综合科学中心人工智能研究所）；Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology（安徽省情感计算与先进智能机器重点实验室，合肥工业大学计算机科学与信息工程学院）；Department of Computer and Network Engineering, The University of Electro-Communications（电子通信大学计算机与网络工程系）
Prompt Disentanglement via Language Guidance and Representation Alignment for Domain Generalization
School of Telecommunications Engineering, the State Key Laboratory of Integrated Services Networks (ISN), Xidian University, Xi’an, China（电信工程学院、集成服务网络国家重点实验室（ISN）、西安电子科技大学）；Microsoft Research Asia, Shanghai, China（微软亚洲研究院，上海，中国）
OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining
Shanghai AI Laboratory（上海人工智能实验室）；University of Strasbourg（斯特拉斯堡大学）；Monash University（莫纳什大学）；University of Michigan（密歇根大学）；Shanghai Jiao Tong University（上海交通大学）；Xiamen University（厦门大学）；The Hong Kong Polytechnic University（香港理工大学）；Technische Universität München（慕尼黑工业大学）
CLIP-AUTT: Test-Time Personalization with Action Unit Prompting for Fine-Grained Video Emotion Recognition
LIVIA, ILLS, Dept. of Systems Engineering, ETS Montreal（LIVIA, ILLS, 系统工程学院, 蒙特利尔高等技术学院）；LIVIA, Dept. of Software and IT Engineering, ETS Montreal（LIVIA, 软件与IT工程学院, 蒙特利尔高等技术学院）；Dept. of Computer Science, École Polytechnique（计算机科学系, 巴黎综合理工学院）
Image-to-Brain Signal Generation for Visual Prosthesis with CLIP Guided Multimodal Diffusion Models
Jinan University, Guangzhou, China；Department of Rehabilitation Medicine, The First Affiliated Hospital of Jinan University, Guangzhou, China；Western University, Ontario, Canada；Guangdong University of Technology, Guangzhou, China；Tsinghua University, Beijing, China
Beijing University of Posts and Telecommunications（北京邮电大学）；S-Lab, Nanyang Technological University（南洋理工大学S-Lab实验室）；The Allen Institute for AI（艾伦人工智能研究所）
