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Coded Event Focal Stack for Continuous Refocusing in Dynamic Scene

delete2026-02-12
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PRE
AI
M
Minggui Teng
S
Suhang Xuan
Z
Zhiang Yan
H
Hanyue Lou
B
Boyu Li
B
Bin Fan
B
Boxin Shi
DOI:10.1109/TPAMI.2026.3664082delete
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Abstract

Abstract

En 中文
Traditional cameras face limitations in maintaining focus across dynamic scenes, especially during rapid motion, due to the constraints of their lenses. Post-capture refocusing techniques, including deep learning-based methods and light field cameras, have been explored to mitigate these challenges. However, these approaches frequently struggle with temporal consistency or experience a trade-off in spatial resolution. In this paper, we introduce the coded event focal stack, a novel approach that captures both motion and depth information through event streams recorded during a modulated focal sweep. Our coded event focal stack enables the generation of full-time intermediate frames refocused at arbitrary focal distances. Extensive experiments on both synthetic and real-world datasets demonstrate the superior refocusing capability of our method over state-of-the-art techniques, particularly in dynamic scenes with complex motion and depth variations.
Keywords:
Computational photography
event camera
image refocusing

Journal

IEEE Transactions on Pattern Analysis and Machine Intelligence cover
IEEE Transactions on Pattern Analysis and Machine Intelligence
IF:
18.6
Papers:
831
Citations:
9.8W

Organization

N
northwestern polytechnical university
Scholars:
1.2W
Papers: 4.3K
Citations: 0
P
peking university
Scholars:
11.7W
Papers: 8.7W
Citations: 146