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Optical-Flow Wingbeat Counting in MuJoCo: A Comparison of Convolutional, Spiking, and Attention-Based Temporal Models

Paper recorded by Signals 4 on 2026-09-15 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.CV · 计算机视觉 · first seen 2026-09-16

Abstract

Visual monitoring of flapping-wing vehicles requires distinguishing individual wingbeats from motion strength and average frequency. This paper presents a controlled MuJoCo evaluation of wingbeat counting from signed optical flow observed by virtual cameras mounted on Crazyflie vehicles. Three flapping-wing models were recorded at optical distances of 1.5 and 3.0 m, producing 1,440 clips from 240

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#35 most recent of 237 cs.CV papers we have recorded · ↑ newer: PanoGS-SLAM: Panoramic 3D Gaussian Splatting SLAM · ↓ older: Semantic-Spatial Agreement Verification for Mitigating Object Hallucin
Cite this page: Optical-Flow Wingbeat Counting in MuJoCo: A Comparison of Convolutional, Spiking, and Attention-Based Temporal Models: the #35 most recent of 237 cs.CV papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/optical-flow-wingbeat-counting-in-mujoco-a-comparison-of-convolutional-spiking-a.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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