Event-based Optical Flow
8 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Event-based Optical Flow
DSEC
Most implemented papers
Event-based Background-Oriented Schlieren
uzh-rpg/event-based_vision_resources
•
•
Schlieren imaging is an optical technique to observe the flow of transparent media, such as air or water, without any particle seeding.
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
chan8972/Spike-FlowNet
•
•
ECCV 2020
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.
Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation
Recently, many deep learning methods have shown great success in providing promising solutions to many event-based problems, such as optical flow estimation.
Real-Time Optical Flow for Vehicular Perception with Low- and High-Resolution Event Cameras
As an answer to these points, we propose an optimized framework for computing optical flow in real-time with both low- and high-resolution event cameras.
Secrets of Event-Based Optical Flow
tub-rip/event_based_optical_flow
•
•
Event cameras respond to scene dynamics and offer advantages to estimate motion.
Event-based Temporally Dense Optical Flow Estimation with Sequential Learning
wponghiran/temporally_dense_flow
•
•
ICCV 2023
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).
TMA: Temporal Motion Aggregation for Event-based Optical Flow
In this paper, we argue that temporal continuity is a vital element of event-based optical flow and propose a novel Temporal Motion Aggregation (TMA) approach to unlock its potential.
IDO-VFI: Identifying Dynamics via Optical Flow Guidance for Video Frame Interpolation with Events
shicy17/ido-vfi
•
•
The proposed method first estimates the optical flow based on frames and events, and then decides whether to further calculate the residual optical flow in those sub-regions via a Gumbel gating module according to the optical flow amplitude.
