Event-based vision: A survey
Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …
[HTML][HTML] Deep learning with spiking neurons: opportunities and challenges
M Pfeiffer, T Pfeil - Frontiers in neuroscience, 2018 - frontiersin.org
Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …
sparse and asynchronous binary signals are communicated and processed in a massively …
Event-based vision meets deep learning on steering prediction for self-driving cars
Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a
scene, filtering out redundant information. This paper presents a deep neural network …
scene, filtering out redundant information. This paper presents a deep neural network …
End-to-end learning of representations for asynchronous event-based data
D Gehrig, A Loquercio, KG Derpanis… - Proceedings of the …, 2019 - openaccess.thecvf.com
Event cameras are vision sensors that record asynchronous streams of per-pixel brightness
changes, referred to as" events". They have appealing advantages over frame based …
changes, referred to as" events". They have appealing advantages over frame based …
Event-based stereo visual odometry
Event-based cameras are bioinspired vision sensors whose pixels work independently from
each other and respond asynchronously to brightness changes, with microsecond …
each other and respond asynchronously to brightness changes, with microsecond …
A unifying contrast maximization framework for event cameras, with applications to motion, depth, and optical flow estimation
We present a unifying framework to solve several computer vision problems with event
cameras: motion, depth and optical flow estimation. The main idea of our framework is to find …
cameras: motion, depth and optical flow estimation. The main idea of our framework is to find …
Secrets of event-based optical flow
Event cameras respond to scene dynamics and offer advantages to estimate motion.
Following recent image-based deep-learning achievements, optical flow estimation methods …
Following recent image-based deep-learning achievements, optical flow estimation methods …
Robust e-nerf: Nerf from sparse & noisy events under non-uniform motion
Event cameras offer many advantages over standard cameras due to their distinctive
principle of operation: low power, low latency, high temporal resolution and high dynamic …
principle of operation: low power, low latency, high temporal resolution and high dynamic …
Spike transformer: Monocular depth estimation for spiking camera
Spiking camera is a bio-inspired vision sensor that mimics the sampling mechanism of the
primate fovea, which has shown great potential for capturing high-speed dynamic scenes …
primate fovea, which has shown great potential for capturing high-speed dynamic scenes …
Deformable neural radiance fields using rgb and event cameras
Abstract Modeling Neural Radiance Fields for fast-moving deformable objects from visual
data alone is a challenging problem. A major issue arises due to the high deformation and …
data alone is a challenging problem. A major issue arises due to the high deformation and …