3D Object
3D object modeling research focuses on accurately and efficiently representing three-dimensional objects from various data sources, including images, point clouds, and sensor data, with primary objectives of reconstruction, manipulation, and understanding. Current research emphasizes the development of novel algorithms and architectures, such as diffusion models, Gaussian splatting, and transformers, to improve the accuracy, efficiency, and generalization capabilities of 3D models, often incorporating multi-view information and physical constraints. These advancements have significant implications for diverse fields, including autonomous driving, robotics, virtual and augmented reality, and medical imaging, by enabling more realistic simulations, improved object recognition, and enhanced human-computer interaction.
Papers
REACTO: Reconstructing Articulated Objects from a Single Video
Chaoyue Song, Jiacheng Wei, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu
Leveraging 3D LiDAR Sensors to Enable Enhanced Urban Safety and Public Health: Pedestrian Monitoring and Abnormal Activity Detection
Nawfal Guefrachi, Jian Shi, Hakim Ghazzai, Ahmad Alsharoa