18.3.1 Event Camera Opeical Flow

Chapter Contents (Back)
Optical Flow. Event Camera.
See also Event Camera.

Almatrafi, M.[Mohammed], Baldwin, R.W.[R. Wes], Aizawa, K.[Kiyoharu], Hirakawa, K.[Keigo],
Distance Surface for Event-Based Optical Flow,
PAMI(42), No. 7, July 2020, pp. 1547-1556.
IEEE DOI 2006
Optical imaging, Optical sensors, Cameras, Voltage control, Neuromorphics, Image edge detection, Surface treatment, neuromorphic camera BibRef

Baldwin, R.W.[R. Wes], Almatrafi, M.[Mohammed], Kaufman, J.R.[Jason R.], Asari, V.[Vijayan], Hirakawa, K.[Keigo],
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras,
ICIAR19(II:395-403).
Springer DOI 1909
BibRef

Shedligeri, P.[Prasan], Mitra, K.[Kaushik],
High frame rate optical flow estimation from event sensors via intensity estimation,
CVIU(208-209), 2021, pp. 103208.
Elsevier DOI 2106
Event sensors, Optical flow, High dynamic range, High temporal resolution BibRef

Brebion, V.[Vincent], Moreau, J.[Julien], Davoine, F.[Franck],
Real-Time Optical Flow for Vehicular Perception With Low- and High-Resolution Event Cameras,
ITS(23), No. 9, September 2022, pp. 15066-15078.
IEEE DOI 2209
Optical sensors, Optical imaging, Image edge detection, Cameras, Sensors, Real-time systems, High-speed optical techniques, real-time applications BibRef

Lin, X.H.[Xiu-Hong], Yang, C.H.[Chen-Hui], Bian, X.S.[Xue-Sheng], Liu, W.Q.[Wei-Quan], Wang, C.[Cheng],
EAGAN: Event-based attention generative adversarial networks for optical flow and depth estimation,
IET-CV(16), No. 7, 2022, pp. 581-595.
DOI Link 2210
BibRef

Liu, M.[Min], Delbruck, T.[Tobi],
EDFLOW: Event Driven Optical Flow Camera With Keypoint Detection and Adaptive Block Matching,
CirSysVideo(32), No. 9, September 2022, pp. 5776-5789.
IEEE DOI 2209
Optical sensors, Voltage control, Cameras, Optical saturation, Optical feedback, Hardware, Estimation, Dynamic vision sensor, FPGA, near-sensor processing BibRef

Pan, L., Liu, M., Hartley, R.I.,
Single Image Optical Flow Estimation With an Event Camera,
CVPR20(1669-1678)
IEEE DOI 2008
Estimation, Cameras, Optical imaging, Brightness, Image reconstruction, Optical variables control, Image restoration BibRef

Wan, Z.X.[Zhe-Xiong], Dai, Y.C.[Yu-Chao], Mao, Y.X.[Yu-Xin],
Learning Dense and Continuous Optical Flow From an Event Camera,
IP(31), 2022, pp. 7237-7251.
IEEE DOI 2212
Optical flow, Estimation, Image motion analysis, Cameras, Correlation, Brightness, Event camera, event-based vision, multimodal learning BibRef

Zhang, Z.L.[Ze-Lin], Yezzi, A.J.[Anthony J.], Gallego, G.[Guillermo],
Formulating Event-Based Image Reconstruction as a Linear Inverse Problem With Deep Regularization Using Optical Flow,
PAMI(45), No. 7, July 2023, pp. 8372-8389.
IEEE DOI 2306
Brightness, Image reconstruction, Cameras, Visualization, Inverse problems, Estimation, Mathematical models, Event cameras, ADMM
See also Event-Based, 6-DOF Camera Tracking from Photometric Depth Maps. BibRef

Gu, D.X.[Da-Xin], Li, J.[Jia], Zhu, L.[Lin], Zhang, Y.[Yu], Ren, J.S.[Jimmy S.],
Reliable Event Generation With Invertible Conditional Normalizing Flow,
PAMI(46), No. 2, February 2024, pp. 927-943.
IEEE DOI 2401
Conditional normalizing flow, contrast threshold, event camera, event generation, event noise rate BibRef


Liu, H.T.[Hao-Tian], Chen, G.[Guang], Qu, S.Q.[San-Qing], Zhang, Y.P.[Yan-Ping], Li, Z.J.[Zhi-Jun], Knoll, A.[Alois], Jiang, C.J.[Chang-Jun],
TMA: Temporal Motion Aggregation for Event-based Optical Flow,
ICCV23(9651-9660)
IEEE DOI Code:
WWW Link. 2401
BibRef

Paredes-Vallés, F.[Federico], Scheper, K.Y.W.[Kirk Y. W.], de Wagter, C.[Christope], de Croon, G.C.H.E.[Guido C. H. E.],
Taming Contrast Maximization for Learning Sequential, Low-latency, Event-based Optical Flow,
ICCV23(9661-9671)
IEEE DOI 2401
BibRef

Schnider, Y.[Yannick], Wozniak, S.[Stanislaw], Gehrig, M.[Mathias], Lecomte, J.[Jules], von Arnim, A.[Axel], Benini, L.[Luca], Scaramuzza, D.[Davide], Pantazi, A.[Angeliki],
Neuromorphic Optical Flow and Real-time Implementation with Event Cameras,
EventVision23(4129-4138)
IEEE DOI 2309
BibRef

Ponghiran, W.[Wachirawit], Liyanagedera, C.M.[Chamika Mihiranga], Roy, K.[Kaushik],
Event-based Temporally Dense Optical Flow Estimation with Sequential Learning,
ICCV23(9793-9802)
IEEE DOI 2401
BibRef

Luo, X.L.[Xing-Long], Luo, K.M.[Kun-Ming], Luo, A.[Ao], Wang, Z.[Zhengning], Tan, P.[Ping], Liu, S.C.[Shuai-Cheng],
Learning Optical Flow from Event Camera with Rendered Dataset,
ICCV23(9813-9823)
IEEE DOI Code:
WWW Link. 2401
BibRef

Nagata, J.[Jun], Sekikawa, Y.[Yusuke],
Tangentially Elongated Gaussian Belief Propagation for Event-Based Incremental Optical Flow Estimation,
CVPR23(21940-21949)
IEEE DOI 2309
BibRef
And: A2, A1:
Live Demonstration: Tangentially Elongated Gaussian Belief Propagation for Event-based Incremental Optical Flow Estimation,
EventVision23(3931-3932)
IEEE DOI 2309
BibRef

Dalgaty, T.[Thomas], Mesquida, T.[Thomas], Joubert, D.[Damien], Sironi, A.[Amos], Vivet, P.[Pascal], Posch, C.[Christoph],
HUGNet: Hemi-Spherical Update Graph Neural Network applied to low-latency event-based optical flow,
EventVision23(3953-3962)
IEEE DOI 2309
BibRef

Li, Z.Y.[Zhuo-Yan], Shen, J.W.[Jia-Wei], Liu, R.[Ruitao],
A Lightweight Network to Learn Optical Flow from Event Data,
ICPR21(1-7)
IEEE DOI 2105
Image motion analysis, Laplace equations, Data integrity, Neural networks, Estimation, Computer architecture, CNN BibRef

Gehrig, M.[Mathias], Millhäusler, M.[Mario], Gehrig, D.[Daniel], Scaramuzza, D.[Davide],
E-RAFT: Dense Optical Flow from Event Cameras,
3DV21(197-206)
IEEE DOI
HTML Version. 2201
Code, Optical Flow. Paper, Video, Code: Training, Image motion analysis, Correlation, Costs, Estimation, Computer architecture, optical flow, event cameras BibRef

Lee, C.[Chankyu], Kosta, A.K.[Adarsh Kumar], Zhu, A.Z.[Alex Zihao], Chaney, K.[Kenneth], Daniilidis, K.[Kostas], Roy, K.[Kaushik],
Spike-flownet: Event-based Optical Flow Estimation with Energy-efficient Hybrid Neural Networks,
ECCV20(XXIX: 366-382).
Springer DOI 2010
BibRef

Zhu, A.Z.[Alex Zihao], Yuan, L.Z.[Liang-Zhe], Chaney, K.[Kenneth], Daniilidis, K.[Kostas],
Unsupervised Event-Based Learning of Optical Flow, Depth, and Egomotion,
CVPR19(989-997).
IEEE DOI 2002
BibRef
Earlier:
Unsupervised Event-Based Optical Flow Using Motion Compensation,
OpticalFlow18(VI:711-714).
Springer DOI 1905
BibRef

Gallego, G., Rebecq, H., Scaramuzza, D.,
A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation,
CVPR18(3867-3876)
IEEE DOI 1812
Trajectory, Estimation, Cameras, Optical imaging, Brightness, Image edge detection BibRef

Ridwan, I.[Iffatur], Cheng, H.[Howard],
An Event-Based Optical Flow Algorithm for Dynamic Vision Sensors,
ICIAR17(182-189).
Springer DOI 1706
BibRef

Chapter on Optical Flow Field Computations and Use continues in
Opeical Flow, Learning, Neural Networks, GAN .


Last update:May 6, 2024 at 15:50:14