Meet NeROIC: An Efficient Artificial Intelligence (AI) Framework

Machine learning is becoming increasingly important in the world of technology. As computers become more advanced and powerful, they can process data faster and more accurately than ever. Recent developments in machine learning have increased interest in using coordinate-based neural networks that parametrize the physical properties of scenes or objects across space and time to solve visual computing problems. These methods, known as neural fields, have been used successfully for synthesizing 3D shapes, human body animation, 3D reconstruction, and pose estimation. The Neural Radiance Fields (NeRF) model, which learns to represent the local opacity and view-dependent radiance of a static scene from sparse calibrated images, is one of the most recent works using neural fields.