Search Results for author:
Found 2 papers, 2 papers with code
Event-based Temporally Dense Optical Flow Estimation with Sequential Learning
In this work, we show that a temporally dense flow estimation at 100Hz can be achieved by treating the flow estimation as a sequential problem using two different variants of recurrent networks - Long-short term memory (LSTM) and spiking neural network (SNN).
DOTIE -- Detecting Objects through Temporal Isolation of Events using a Spiking Architecture
Our technique consists of a lightweight spiking neural architecture that is able to separate events based on the speed of the corresponding objects.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
