Papers Event-based Optical Flow
“Event-based Optical Flow” 태그가 달린 논문 41편 · 필터 해제
Event-based Motion & Appearance Fusion for 6D Object Pose Tracking
Object pose tracking is a fundamental and essential task for robotics to perform tasks in the home and industrial settings. The most commonly used sensors to do so are RGB-D cameras, which can hit limitations in highly d…
Event-based Optical FlowPose TrackingUEOF: A Benchmark Dataset for Underwater Event-Based Optical Flow
Underwater imaging is fundamentally challenging due to wavelength-dependent light attenuation, strong scattering from suspended particles, turbidity-induced blur, and non-uniform illumination. These effects impair standa…
Event-based Optical FlowDESSERT: Diffusion-based Event-driven Single-frame Synthesis via Residual Training
Video frame prediction extrapolates future frames from previous frames, but suffers from prediction errors in dynamic scenes due to the lack of information about the next frame. Event cameras address this limitation by c…
Video Frame InterpolationEvent-based Optical FlowInertia-Informed Orientation Priors for Event-Based Optical Flow Estimation
Event cameras, by virtue of their working principle, directly encode motion within a scene. Many learning-based and model-based methods exist that estimate event-based optical flow, however the temporally dense yet spati…
Event-based Optical Flow6-DoF Object Tracking with Event-based Optical Flow and Frames
Tracking the position and orientation of objects in space (i.e., in 6-DoF) in real time is a fundamental problem in robotics for environment interaction. It becomes more challenging when objects move at high-speed due to…
Event-based Optical FlowPose EstimationObject TrackingPose TrackingSpatio-Temporal State Space Model For Efficient Event-Based Optical Flow
Event cameras unlock new frontiers that were previously unthinkable with standard frame-based cameras. One notable example is low-latency motion estimation (optical flow), which is critical for many real-time application…
Computational EfficiencyEvent-based Optical FlowMotion EstimationOptical Flow Estimation+1eStonefish-scenes: A synthetically generated dataset for underwater event-based optical flow prediction tasks
The combined use of event-based vision and Spiking Neural Networks (SNNs) is expected to significantly impact robotics, particularly in tasks like visual odometry and obstacle avoidance. While existing real-world event-b…
Event-based Optical FlowEvent-based visionOptical Flow EstimationVisual OdometryPlanar Velocity Estimation for Fast-Moving Mobile Robots Using Event-Based Optical Flow
Accurate velocity estimation is critical in mobile robotics, particularly for driver assistance systems and autonomous driving. Wheel odometry fused with Inertial Measurement Unit (IMU) data is a widely used method for v…
Autonomous DrivingAutonomous RacingEvent-based Optical FlowOptical Flow EstimationNonlinear Motion-Guided and Spatio-Temporal Aware Network for Unsupervised Event-Based Optical Flow
Event cameras have the potential to capture continuous motion information over time and space, making them well-suited for optical flow estimation. However, most existing learning-based methods for event-based optical fl…
Event-based Optical FlowMotion CompensationOptical Flow EstimationPerturbed State Space Feature Encoders for Optical Flow with Event Cameras
With their motion-responsive nature, event-based cameras offer significant advantages over traditional cameras for optical flow estimation. While deep learning has improved upon traditional methods, current neural networ…
Event-based Optical FlowOptical Flow EstimationSpatial ReasoningST-FlowNet: An Efficient Spiking Neural Network for Event-Based Optical Flow Estimation
Spiking Neural Networks (SNNs) have emerged as a promising tool for event-based optical flow estimation tasks due to their ability to leverage spatio-temporal information and low-power capabilities. However, the performa…
Event-based Optical FlowOptical Flow EstimationBAT: Learning Event-based Optical Flow with Bidirectional Adaptive Temporal Correlation
Event cameras deliver visual information characterized by a high dynamic range and high temporal resolution, offering significant advantages in estimating optical flow for complex lighting conditions and fast-moving obje…
Event-based Optical FlowOptical Flow EstimationEDCFlow: Exploring Temporally Dense Difference Maps for Event-based Optical Flow Estimation
Recent learning-based methods for event-based optical flow estimation utilize cost volumes for pixel matching but suffer from redundant computations and limited scalability to higher resolutions for flow refinement. …
Event-based Optical FlowOptical Flow EstimationeCARLA-scenes: A synthetically generated dataset for event-based optical flow prediction
The joint use of event-based vision and Spiking Neural Networks (SNNs) is expected to have a large impact in robotics in the near future, in tasks such as, visual odometry and obstacle avoidance. While researchers have u…
DiversityEvent-based Optical FlowEvent-based visionOptical Flow Estimation+1SDformerFlow: Spatiotemporal swin spikeformer for event-based optical flow estimation
Event cameras generate asynchronous and sparse event streams capturing changes in light intensity. They offer significant advantages over conventional frame-based cameras, such as a higher dynamic range and an extremely …
Event-based Optical FlowOptical Flow EstimationEMatch: A Unified Framework for Event-based Optical Flow and Stereo Matching
Event cameras have shown promise in vision applications like optical flow estimation and stereo matching, with many specialized architectures leveraging the asynchronous and sparse nature of event data. However, existing…
Depth EstimationDisparity EstimationEvent-based Optical FlowOptical Flow Estimation+2Event-based Optical Flow on Neuromorphic Processor: ANN vs. SNN Comparison based on Activation Sparsification
Spiking neural networks (SNNs) for event-based optical flow are claimed to be computationally more efficient than their artificial neural networks (ANNs) counterparts, but a fair comparison is missing in the literature. …
Event-based Optical FlowOptical Flow EstimationVector-Symbolic Architecture for Event-Based Optical Flow
From a perspective of feature matching, optical flow estimation for event cameras involves identifying event correspondences by comparing feature similarity across accompanying event frames. In this work, we introduces a…
Event-based Optical FlowOptical Flow EstimationSelf-Supervised LearningEvent-based Background-Oriented Schlieren
Schlieren imaging is an optical technique to observe the flow of transparent media, such as air or water, without any particle seeding. However, conventional frame-based techniques require both high spatial and temporal …
Event-based Optical FlowEvent-based visionOptical Flow EstimationS-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural Networks
Spiking Neural Networks (SNNs) are biologically plausible models that have been identified as potentially apt for deploying energy-efficient intelligence at the edge, particularly for sequential learning tasks. However, …
Audio ClassificationEvent-based Optical FlowGesture RecognitionImage Classification+1