Event cameras are bio-inspired sensors that asynchronously report intensity changes in
microsecond resolution. DAVIS can capture high dynamics of a scene and simultaneously …

Event cameras such as DAVIS can simultaneously output high temporal resolution events
and low frame-rate intensity images, which own great potential in capturing scene motion …

Optical flow estimation is a crucial task in computer vision that provides low-level motion
information. Despite recent advances, real-world applications still present significant …

Event cameras respond to scene dynamics and offer advantages to estimate motion.
Following recent image-based deep-learning achievements, optical flow estimation methods …

To date, top-performing optical flow estimation methods only take pairs of consecutive
frames into account. While elegant and appealing, the idea of using more than two frames …

Motion analysis is one of the most fundamental and challenging problems in the field of
computer vision, which can be widely applied in many areas, such as autonomous driving …

Event-based cameras have shown great promise in a variety of situations where frame
based cameras suffer, such as high speed motions and high dynamic range scenes …

Many successful optical flow estimation methods have been proposed, but they become
invalid when tested in dark scenes because low-light scenarios are not considered when …

Event camera has offered promising alternative for visual perception, especially in high
speed and high dynamic range scenes. Recently, many deep learning methods have shown …

We learn to compute optical flow by combining a classical spatial-pyramid formulation with
deep learning. This estimates large motions in a coarse-to-fine approach by warping one …