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Neural-based scene reconstruction and synthesis using event cameras
The project will focus on exploring the use of event-based cameras in neural-based scene reconstruction and synthesis, extending available approaches to event-based data.
Purely learning-based methods leveraging implicit scene representations have shown impressive results in the reconstruction and synthesis of complex scenes from just a few images, largely surpassing those of traditional methods such as Structure-from-motion, photogrammetry, and image-based rendering. Due to their recent introduction, their advantages over traditional methods are still being explored in the field of computer vision. In particular, their use in conjunction with event-based cameras, bio-inspired sensors with improved latency, temporal resolution, and dynamic range, is still under-explored.
Purely learning-based methods leveraging implicit scene representations have shown impressive results in the reconstruction and synthesis of complex scenes from just a few images, largely surpassing those of traditional methods such as Structure-from-motion, photogrammetry, and image-based rendering. Due to their recent introduction, their advantages over traditional methods are still being explored in the field of computer vision. In particular, their use in conjunction with event-based cameras, bio-inspired sensors with improved latency, temporal resolution, and dynamic range, is still under-explored.
The project will focus on exploring the use of event-based cameras in neural-based scene reconstruction and synthesis, extending available approaches to event-based data. We look for students with strong programming (Pyhton/Matlab) and computer vision background. Additionally, knowledge of machine learning frameworks (pytorch, tensorflow) is required.
The project will focus on exploring the use of event-based cameras in neural-based scene reconstruction and synthesis, extending available approaches to event-based data. We look for students with strong programming (Pyhton/Matlab) and computer vision background. Additionally, knowledge of machine learning frameworks (pytorch, tensorflow) is required.