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Many underwater applications, such as offshore asset inspections, rely on visual inspection and detailed 3D reconstruction.
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G. Gallego, H. Rebecq, and D. Scaramuzza, “A unifying contrast maximization framework for event cameras, with applications to motion, depth, and optical flow estimation,” in Proceedings of the IEEE conference on computer vision and pattern recognition
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K. A. Skinner, J. Zhang, E. A. Olson, and M. Johnson-Roberson, “Uwstereonet: Unsupervised learning for depth estimation and color correction of underwater stereo imagery,” in 2019 International Conference on Robotics and Automation (ICRA)
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T. Qin, J. Pan, S. Cao, and S. Shen, “A general optimization-based framework for local odometry estimation with multiple sensors,” 2019
2019
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S. Rahman, A. Q. Li, and I. Rekleitis, “Svin2: An underwater slam system using sonar, visual, inertial, and depth sensor,” in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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D. Berman, D. Levy, S. Avidan, and T. Treibitz, “Underwater single image color restoration using haze-lines and a new quantitative dataset,” IEEE transactions on pattern analysis and machine intelligence
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G. Gallego, T. Delbrück, G. Orchard, C. Bartolozzi, B. Taba, A. Censi, S. Leutenegger, A. J. Davison, J. Conradt, K. Daniilidis, and D. Scaramuzza, “Event-based vision: A survey,” IEEE Transactions on Pattern Analysis and Machine Intelligence
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2023
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2023
Later among the works it cites.
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M. J. Islam, C. Edge, Y. Xiao, P. Luo, M. Mehtaz, C. Morse, S. S. Enan, and J. Sattar, “Semantic segmentation of underwater imagery: Dataset and benchmark,” in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2020
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J. Niu, S. Zhong, X. Lu, S. Shen, G. Gallego, and Y. Zhou, “Esvo2: Direct visual-inertial odometry with stereo event cameras,” IEEE Transactions on Robotics
2025
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