Learning to represent scenes with geometry and semantics - Wang, B (2022)
Scene representation is the process of converting sensory observations of an environment into compact descriptions. Such intelligent behavior is a cornerstone of artificial intelligence. Scientists have long sought to reproduce the extraordinary ability of humans for understanding the physical environment. Taking visual sensory observations of an environment as input, modern intelligent systems mostly aim to learn neural representations that encode fundamental scene properties such as geometry and semantics. Such representations can be leveraged to support other downstream tasks and finally realize autonomous perception and interaction within the complex 3D world.