This paper presents dataset characteristics such as head pose, gaze direction, and pupil size. Furthermore, it introduces a hybrid frame-event based gaze estimation method specifically designed for the collected dataset. Moreover, it performs extensive evaluations of different benchmarking methods under various gaze-related factors.
Synthetic Lunar Terrain (SLT) is an open dataset collected from an analogue test site for lunar missions, featuring synthetic craters in a high-contrast lighting setup. It includes several side-by-side captures from event-based and conventional RGB cameras, supplemented with a high-resolution 3D laser scan for depth estimation.
Low-light environments pose significant challenges for image enhancement methods. To address these challenges, this work introduces the HUE dataset, a comprehensive collection of high-resolution event and frame sequences captured in diverse and challenging low-light conditions.
Low-light environments pose significant challenges for image enhancement methods. To address these challenges, this work introduces the HUE dataset, a comprehensive collection of high-resolution event and frame sequences captured in diverse and challenging low-light conditions.
This papers addresses the lack of datasets by introducing eWiz, a comprehensive library for processing event-based data. It includes tools for data loading, augmentation, visualization, encoding, and generation of training data, along with loss functions and performance metrics.
This paper proposes a novel, computationally efficient regularizer to mitigate event collapse in the CMax framework. From a theoretical point of view, the regularizer is designed based on geometric principles of motion field deformation (measuring area rate of change along point trajectories).