In this study, we tackle the challenge of classifying the object category in point clouds, which previous works like PointCLIP struggle to address due to the inherent limitations of the CLIP architecture. Our approach leverages GPT-4 Vision (GPT-4V) to overcome these challenges by employing its advanced generative abilities, enabling a more adaptive and robust classification process. We adapt the application of GPT-4V to process complex 3D data, enabling it to achieve zero-shot recognition capabilities without altering the underlying model architecture. Our methodology also includes a systematic strategy for point cloud image visualization, mitigating domain gap and enhancing GPT-4V's efficiency. Experimental validation demonstrates our approach's superiority in diverse scenarios, setting a new benchmark in zero-shot point cloud classification.
VTG-GPT: Tuning-Free Zero-Shot Video Temporal Grounding with GPT
School of Electronic Science and Engineering, Nanjing University（南京大学电子科学与工程学院）；School of Physics and Electronics, Hubei Normal University（湖北师范大学物理与电子科学学院）
TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation
Sichuan University（四川大学）；Case Western Reserve University（凯斯西储大学）；Beijing University of Posts and Telecommunications（北京邮电大学）；Urgench State University（乌尔根奇国立大学）；Gansu Agricultural University（甘肃农业大学）
Object Counting with GPT-4o and GPT-5: A Comparative Study
Software Engineering Institute, Obuda University, Budapest, Hungary（奥布达大学软件工程研究所）；Doctoral School of Applied Informatics（应用信息科学博士学院）；Applied Mathematics, Obuda University, Budapest, Hungary（应用数学，奥布达大学）；John von Neumann Faculty of Informatics, Obuda University, Budapest, Hungary（约翰·冯·诺伊曼信息学院，奥布达大学）；Faculty of Economics（经济学院）
GPT4Ego: Unleashing the Potential of Pre-trained Models for Zero-Shot Egocentric Action Recognition
School of Computer Science and Engineering, Nanjing University of Science and Technology（南京理工大学计算机科学与工程学院）；School of Computer Science, The University of Sydney（悉尼大学计算机科学学院）；Department of Computer Science and Technology, Nanjing University（南京大学计算机科学与技术系）；Artificial Intelligence Industrial Technology Research Institute, Nanjing Institute of Technology（南京工程学院人工智能产业技术研究院）
Few-shot medical image classification with simple shape and texture text descriptors using vision-language models
RIKEN Center for Brain Science（理化学研究所脑科学中心）；Institute of Fundamental Technological Research, Polish Academy of Sciences（波兰科学院基础技术研究所）；Faculty of Computer Science, Universitas Indonesia（印度尼西亚大学计算机学院）
GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Software Engineering Institute, Peking University（北京大学软件工程研究所）；Department of Automation, Tsinghua University（清华大学自动化系）；Beijing National Research Center for Information Science and Technology, Tsinghua University（清华大学北京信息科学与技术国家研究中心）
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；City University of Hong Kong（香港城市大学）；Yale University（耶鲁大学）；Peking University（北京大学）；The Chinese University of Hong Kong（香港中文大学）
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
Northwestern Polytechnical University（西北工业大学）；School of Computer Science and Engineering, University of Electronic Science and Technology of China（电子科技大学计算机科学与工程学院）；Centre for Frontier AI Research, A*STAR（新加坡科技研究局前沿人工智能研究中心）；Nanyang Technological University（南洋理工大学）
Exploiting Temporal Audio-Visual Correlation Embedding for Audio-Driven One-Shot Talking Head Animation
School of Information Engineering, Guangdong University of Technology（广东工业大学信息工程学院）；School of Computer Science and Engineering, Sun Yat-sen University（中山大学计算机科学与工程学院）
Prompt to Protection: A Comparative Study of Multimodal LLMs in Construction Hazard Recognition
Department of Construction Management, Colorado State University（科罗拉多州立大学建设管理系）；Department of Civil, Construction, and Environmental Engineering, North Carolina State University（北卡罗来纳州立大学土木、建设与环境工程系）
