With the exponential increase in video content, the need for accurate deception detection in human-centric video analysis has become paramount. This research focuses on the extraction and combination of various features to enhance the accuracy of deception detection models. By systematically extracting features from visual, audio, and text data, and experimenting with different combinations, we developed a robust model that achieved an impressive 99% accuracy. Our methodology emphasizes the significance of feature engineering in deception detection, providing a clear and interpretable framework. We trained various machine learning models, including LSTM, BiLSTM, and pre-trained CNNs, using both single and multi-modal approaches. The results demonstrated that combining multiple modalities significantly enhances detection performance compared to single modality training. This study highlights the potential of strategic feature extraction and combination in developing reliable and transparent automated deception detection systems in video analysis, paving the way for more advanced and accurate detection methodologies in future research.
Despite a revolution in the pervasiveness of video cameras in our daily lives, one of the most meaningful forms of nonverbal affective communication, interpersonal eye gaze, i.e. eye gaze relative to a conversation partner, is not available from common video. We introduce the Interpersonal-Calibrating Eye-gaze Encoder (ICE), which automatically extracts interpersonal gaze from video recordings without specialized hardware and without prior knowledge of participant locations. Leveraging the intuition that individuals spend a large portion of a conversation looking at each other enables the ICE …
BTCChat: Advancing Remote Sensing Bi-temporal Change Captioning with Multimodal Large Language Model
State Key Laboratory of Networking and Switching Technology（网络与交换技术国家重点实验室）；Beijing University of Posts and Telecommunications（北京邮电大学）；Aerospace Information Research Institute（航天信息研究所）；Chinese Academy of Sciences（中国科学院）；School of Geographical Sciences（地理科学学院）；Hunan Normal University（湖南师范大学）
Dual Frequency Branch Framework with Reconstructed Sliding Windows Attention for AI-Generated Image Detection
Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology（数字取证工程研究中心，教育 ministry，南京信息科学技术大学）
ABCDWaveNet: Advancing Robust Road Ponding Detection in Fog through Dynamic Frequency-Spatial Synergy
Sun Yat-sen University（中山大学）；Nanyang Technological University（南洋理工大学）；Western Power（西部电力公司）；Tsinghua University（清华大学）；Harbin Institute of Technology（哈尔滨工业大学）
Hyperspectral Image Spectral-Spatial Feature Extraction via Tensor Principal Component Analysis
School of Electronics and Information, Zhongyuan University of Technology（中原工学院电子与信息学院）；Birkbeck College, University of London（伦敦大学伯克贝克学院）；School of Computer Science, Northwestern Polytechnical University（西北工业大学计算机学院）；Information Center of the Yellow River Conservancy Commission（黄河水利委员会信息中心）
Intelligent Vision and Sensing (IVS) Lab at SUNY Binghamton（SUNY布林茅伊大学智能视觉与感知实验室）；Yancheng Institute of Technology（盐城职业技术学院）；University of Georgia（佐治亚大学）
Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing
Arab American University（阿拉伯美国大学）；Columbia University（哥伦比亚大学）；Budapest University of Technology and Economics（布达佩斯技术与经济大学）；Al-Ahliyya Amman University（阿赫利耶阿曼大学）；Queensland University of Technology（昆士兰科技大学）
ClinicalFMamba: Advancing Clinical Assessment using Mamba-based Multimodal Neuroimaging Fusion
TD Bank Group, Toronto, Canada（TD银行集团，加拿大）；Department of Computer Science, University of Toronto, Toronto, Canada（多伦多大学计算机科学系，加拿大）；Department of Medical Imaging, University of Toronto, Toronto, Canada（多伦多大学医学影像系，加拿大）
Advancing Out-of-Distribution Detection through Data Purification and Dynamic Activation Function Design
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）；University of Chinese Academy of Sciences（中国科学院大学）；Zhejiang University（浙江大学）
LMM-VQA: Advancing Video Quality Assessment with Large Multimodal Models
Institute of Image Communication and Information Processing, Shanghai Jiao Tong University（上海交通大学图像通信与信息处理研究所）；MoE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University（上海交通大学人工智能研究院（教育部人工智能重点实验室））；Huawei Technologies（华为技术有限公司）
A Large-Language-Model Assisted Automated Scale Bar Detection and Extraction Framework for Scanning Electron Microscopic Images
Shanghai Jiao Tong Global College（上海交通大学全球学院）；Shanghai Jiao Tong University（上海交通大学）；Global Institute of Future Technology（全球未来技术研究院）；AI Lab, Xiaomi Corporation（小米公司AI实验室）
