arXiv:1907.04060
Event-based attention and tracking on neuromorphic hardware
원문 초록
We present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic Vision Sensor DAVIS. The attention mechanism is realized as a recurrent spiking neural network that implements attractor-dynamics of dynamic neural fields. We demonstrate capability of the system to create sustained activation that supports object tracking when distractors are present or when the object slows down or stops, reducing the number of generated events.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
RGBTrack: Fast, Robust Depth-Free 6D Pose Estimation and Tracking
ReaMOT: A Benchmark and Framework for Reasoning-based Multi-Object Tracking
EOTNet: Deep Memory Aided Bayesian Filter for Extended Object Tracking
Asynchronous Multi-Object Tracking with an Event Camera
A Simple Detector with Frame Dynamics is a Strong Tracker
LLM-Empowered Embodied Agent for Memory-Augmented Task Planning in Household Robotics
토론
이 논문과 연결된 포럼 글이 아직 없습니다.