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… Read More »Retail store dataset augmentation

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… Read More »Supervised City Mesh texturing via deep neural networks

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… Read More »Real-time understanding of outdoor environments

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… Read More »Semantic 3D Segmentation for Scene Understanding

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… Read More »Reconstruction and texturing of humans using deep neural networks

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… Read More »Object and Scene Synthesis via deep neural networks

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,… Read More »Urban Semantic Understanding