High-speed Imaging through Turbulence with Event-based Light Fields

arXiv:2603.14023 · cs.CV · Submitted 2026-03-14 · Read on arXiv

cs.CV

Submitted: 2026-03-14

Updated: 2026-09-22

Project page: https://justhowww.github.io/lf-ev-turb-project-page

Terminology

• Aperture — 20× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 6× in this paper
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 2× in this paper
• Calibration — 2× in this paper · explained in 7 episodes
• Hypernetwork — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Adaptive Optics (AO) — 1× in this paper · explained in 2 episodes
• Coherence Length — 1× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Optical Flow — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes

Sources

• Guidestar-Free Adaptive Optics with Asymmetric Apertures
• EGTM: Event-guided Efficient Turbulence Mitigation
• EvTurb: Event Camera Guided Turbulence Removal
• Neuromorphic Shack-Hartmann wave normal sensing
• Spectral Norm Regularization for Improving the Generalizability of Deep Learning

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