The need to incorporate artificial intelligence in real-life scenarios and essentially improve the quality of various industry business services rise the need to develop datasets that fit very specific different…

Supervised deep learning approaches sometimes is limited due to the lack of data for specific tasks and researchers flee in unsupervised approaches as sometimes to create datasets that contain the…

One of the main research challenges in the area of autonomous navigation (e.g. self-driving cars), is the real-time processing and understanding of 3D point clouds captured by LiDAR (Light Detection And Ranging) sensors…

Semantic 3D segmentation is a task essential to applications that require an understanding of real-world 3D scenes, such as robotics, artificial intelligence (AI), augmented or virtual reality (AR/VR), and autonomous…

Capturing the shape and appearance of a human has been a significant first step for applications such as clothing fitting, avatar creation, and fitness, to name a few. With the…

Synthesizing 3D objects and 3D scenes has received a great deal of attention in recent years due to its applications in simulation, AI, robotics and 3D modelling. Recent work has…

Semantic understanding of urban data (e.g. buildings, streets, neighborhoods) is critical for urban sensing as well as many commercial applications such as accurate antenna placement for cellular networks, flood planning, and architectural urban visualisations.…