Semantic Scene

Semantic scene understanding aims to computationally interpret the meaning and context within visual scenes, encompassing object recognition, spatial relationships, and scene semantics. Current research heavily focuses on developing robust and efficient models, often employing deep learning architectures like transformers and neural networks, for tasks such as semantic segmentation, scene completion, and object detection across various sensor modalities (RGB, LiDAR, thermal). This field is crucial for advancing autonomous systems (driving, robotics), improving human-computer interaction, and enabling new applications in areas like augmented reality and remote sensing, driving progress in both computer vision and related fields.