FracEvent: Event-Camera Simulation via Fractional-Relaxation Pixel Dynamics

2026-06-25

AI Summary

This work addresses the challenge of limited availability of real event camera data and the temporal inaccuracies introduced by existing simulation methods, which oversimplify pixel-level dynamics and consequently hinder downstream task performance. To overcome this, the authors propose a novel event camera simulation framework grounded in fractional-order relaxation voltage dynamics. By modeling the full pixel lifecycle and incorporating a memory-aware fractional-order relaxation mechanism, the method more faithfully captures voltage evolution through log-intensity-driven multimodal responses, continuous voltage threshold crossing detection, and a memory-informed reference level update strategy. Experimental results demonstrate that the generated event streams exhibit superior temporal fidelity and significantly outperform existing simulators in image reconstruction and optical flow estimation tasks.

Abstract

Event cameras asynchronously report brightness changes with microsecond-level temporal resolution, but real event data remain difficult to collect at scale because specialized sensors, careful synchronization, and task-specific annotations are required. Event-camera simulation is therefore important to event-based vision tasks. Most practical simulators build on contrast-threshold event generation, some with additional filtering, stochastic noise, or hand-tuned sensor parameters. While effective, such formulations often simplify the temporal structure produced by the lifecycle of each pixel, which can distort event timing and weaken downstream transfer. We introduce FracEvent, an event simulator that models this pixel-level lifecycle with fractional-relaxation voltage dynamics. Given a log-intensity trajectory, FracEvent drives a compact stack of relaxation modes, combines their responses into a voltage state, emits ON/OFF events by localizing threshold crossings on the continuous voltage trajectory, and updates the reference while retaining the underlying memory modes. This retained state links residual voltage response to later event timing. We evaluate FracEvent through event-stream comparison and downstream transfer on image reconstruction and optical flow estimation. Across multiple datasets, FracEvent improves the temporal structure of generated events and achieves stronger downstream-transfer results than competing simulator baselines, showing its practical value for event-camera simulation.

Problem

• event camera simulation
• temporal structure
• pixel dynamics
• event timing
• downstream transfer

Innovation

• event camera simulation
• fractional relaxation
• pixel dynamics
• temporal structure
• voltage trajectory