Search Results for author:
Found 7 papers, 6 papers with code
Event-based Continuous Color Video Decompression from Single Frames
We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image, using an event camera.
EvAC3D: From Event-based Apparent Contours to 3D Models via Continuous Visual Hulls
3D reconstruction from multiple views is a successful computer vision field with multiple deployments in applications.
Semantic keypoint-based pose estimation from single RGB frames
Empirically, we show that our approach can accurately recover the 6-DoF object pose for both instance- and class-based scenarios even against a cluttered background.
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
Spiking Neural Networks (SNNs) serve as ideal paradigms to handle event camera outputs, but deep SNNs suffer in terms of performance due to the spike vanishing phenomenon.
Minibatch Processing in Spiking Neural Networks
To our knowledge, this is the first general-purpose implementation of mini-batch processing in a spiking neural networks simulator, which works with arbitrary neuron and synapse models.
Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotion
In this work, we propose a novel framework for unsupervised learning for event cameras that learns motion information from only the event stream.
EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras
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.
