Event Camera Calibration,
2021
Online
WWW Link. And the workshop paper to appear.
PDF File.
2106
Toolbox to facilitate event camera calibration.
The framework uses neural network-based image reconstruction to enable
compatibility with any existing calibration toolbox.
BibRef
Barranco, F.[Francisco],
Fermüller, C.[Cornelia],
Aloimonos, Y.F.[Yi-Fannis],
Contour Motion Estimation for Asynchronous Event-Driven Cameras,
PIEEE(102), No. 10, October 2014, pp. 1537-1556.
IEEE DOI
1410
BibRef
Barranco, F.[Francisco],
Teo, C.L.,
Fermüller, C.[Cornelia],
Aloimonos, Y.F.[Yi-Fannis],
Contour Detection and Characterization for Asynchronous Event Sensors,
ICCV15(486-494)
IEEE DOI
1602
BibRef
Liu, H.C.[Han-Chao],
Zhang, F.L.[Fang-Lue],
Marshall, D.[David],
Shi, L.P.[Lu-Ping],
Hu, S.M.[Shi-Min],
High-speed video generation with an event camera,
VC(33), No. 6-8, June 2017, pp. 749-759.
Springer DOI
1706
Only record events when the light on a pixel changes. Good for high speed
images, but incomplete data.
BibRef
Munda, G.[Gottfried],
Reinbacher, C.[Christian],
Pock, T.[Thomas],
Real-Time Intensity-Image Reconstruction for Event Cameras Using
Manifold Regularisation,
IJCV(126), No. 12, December 2018, pp. 1381-1393.
Springer DOI
1811
BibRef
Reinbacher, C.[Christian],
Graber, G.[Gottfried],
Pock, T.[Thomas],
Real-Time Intensity-Image Reconstruction for Event Cameras Using
Manifold Regularisation,
BMVC16(xx-yy).
DOI Link
1805
From per-pixel intensity changes, not intensity level.
The inverse of change detection.
BibRef
Gallego, G.[Guillermo],
Lund, J.E.A.[Jon E.A.],
Mueggler, E.[Elias],
Rebecq, H.[Henri],
Delbruck, T.[Tobi],
Scaramuzza, D.[Davide],
Event-Based, 6-DOF Camera Tracking from Photometric Depth Maps,
PAMI(40), No. 10, October 2018, pp. 2402-2412.
IEEE DOI
1809
Cameras, Standards, Tracking, Voltage control, Robot vision systems,
Event-based vision, pose tracking, dynamic vision sensor,
AR/VR
See also Formulating Event-Based Image Reconstruction as a Linear Inverse Problem With Deep Regularization Using Optical Flow.
BibRef
Rebecq, H.[Henri],
Gallego, G.[Guillermo],
Scaramuzza, D.[Davide],
EMVS: Event-based Multi-View Stereo,
BMVC16(xx-yy).
HTML Version.
1805
Stereo with event (pixel change, not value) cameras.
BibRef
Rebecq, H.[Henri],
Ranftl, R.[René],
Koltun, V.[Vladlen],
Scaramuzza, D.[Davide],
High Speed and High Dynamic Range Video with an Event Camera,
PAMI(43), No. 6, June 2021, pp. 1964-1980.
IEEE DOI
2106
BibRef
Earlier:
Events-To-Video: Bringing Modern Computer Vision to Event Cameras,
CVPR19(3852-3861).
IEEE DOI
2002
Code, HDR.
Dataset, HDR.
Dataset, E2VID.
HTML Version. Image reconstruction, Cameras, Streaming media, Dynamic range,
Brightness, Heuristic algorithms,
high dynamic range
BibRef
Messikommer, N.[Nico],
Georgoulis, S.[Stamatios],
Gehrig, D.[Daniel],
Tulyakov, S.[Stepan],
Erbach, J.[Julius],
Bochicchio, A.[Alfredo],
Li, Y.Y.[Yuan-You],
Scaramuzza, D.[Davide],
Multi-Bracket High Dynamic Range Imaging with Event Cameras,
NTIRE22(546-556)
IEEE DOI
2210
Image resolution, Fuses, Pipelines, Dynamic range,
Cameras, Robustness
BibRef
Rebecq, H.[Henri],
Gallego, G.[Guillermo],
Mueggler, E.[Elias],
Scaramuzza, D.[Davide],
EMVS: Event-Based Multi-View Stereo: 3D Reconstruction with an Event
Camera in Real-Time,
IJCV(126), No. 12, December 2018, pp. 1394-1414.
Springer DOI
1811
BibRef
Peng, X.[Xin],
Wang, Y.[Yifu],
Gao, L.[Ling],
Kneip, L.[Laurent],
Globally-optimal Event Camera Motion Estimation,
ECCV20(XXVI:51-67).
Springer DOI
2011
BibRef
Zhou, Y.[Yi],
Gallego, G.[Guillermo],
Rebecq, H.[Henri],
Kneip, L.[Laurent],
Li, H.D.[Hong-Dong],
Scaramuzza, D.[Davide],
Semi-dense 3D Reconstruction with a Stereo Event Camera,
ECCV18(I: 242-258).
Springer DOI
1810
BibRef
Zebhi, S.[Saeedeh],
Al-Modarresi, S.M.T.,
Abootalebi, V.[Vahid],
Converting video classification problem to image classification with
global descriptors and pre-trained network,
IET-CV(14), No. 8, December 2020, pp. 614-624.
DOI Link
2012
Use a motion history image.
BibRef
Cadena, P.R.G.,
Qian, Y.,
Wang, C.,
Yang, M.,
SPADE-E2VID: Spatially-Adaptive Denormalization for Event-Based Video
Reconstruction,
IP(30), 2021, pp. 2488-2500.
IEEE DOI
2102
Image reconstruction, Cameras, Training, Image resolution,
Task analysis, Optical losses, Brightness, Image reconstruction,
sparse image
BibRef
Gallego, G.[Guillermo],
Delbrück, T.[Tobi],
Orchard, G.[Garrick],
Bartolozzi, C.[Chiara],
Taba, B.[Brian],
Censi, A.[Andrea],
Leutenegger, S.[Stefan],
Davison, A.J.[Andrew J.],
Conradt, J.[Jörg],
Daniilidis, K.[Kostas],
Scaramuzza, D.[Davide],
Event-Based Vision: A Survey,
PAMI(44), No. 1, January 2022, pp. 154-180.
IEEE DOI
2112
Cameras, Voltage control, Brightness, Robot vision systems, Retina,
Event cameras, bio-inspired vision, asynchronous sensor,
low power
BibRef
Pan, L.Y.[Li-Yuan],
Hartley, R.I.[Richard I.],
Scheerlinck, C.[Cedric],
Liu, M.M.[Miao-Miao],
Yu, X.[Xin],
Dai, Y.C.[Yu-Chao],
High Frame Rate Video Reconstruction Based on an Event Camera,
PAMI(44), No. 5, May 2022, pp. 2519-2533.
IEEE DOI
2204
BibRef
Earlier: A1, A3, A5, A2, A4, A6:
Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera,
CVPR19(6813-6822).
IEEE DOI
2002
Image reconstruction, Cameras, Image resolution, Data models,
Optimization, Image restoration, Lighting, Event camera (DAVIS),
fibonacci sequence
BibRef
Li, Z.[Zeyu],
Liu, Y.[Yong],
Zhou, F.[Feng],
Li, X.W.[Xiao-Wan],
Intensity/Inertial Integration-Aided Feature Tracking on Event
Cameras,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Iaboni, C.[Craig],
Patel, H.[Himanshu],
Lobo, D.[Deepan],
Choi, J.W.[Ji-Won],
Abichandani, P.[Pramod],
Where Are They Going? Clustering Event Camera Data to Detect and
Track Moving Objects,
Computer(55), No. 6, June 2022, pp. 90-94.
IEEE DOI
2206
Tutorial.
Use of event cameras with frame-based algorithms.
BibRef
Schiopu, I.[Ionut],
Bilcu, R.C.[Radu Ciprian],
Lossless Compression of Event Camera Frames,
SPLetters(29), 2022, pp. 1779-1783.
IEEE DOI
2208
Cameras, Electromagnetic interference, Symbols, Image coding,
Indexes, Encoding, Context modeling, Lossless coding, event camera
BibRef
Schiopu, I.[Ionut],
Bilcu, R.C.[Radu Ciprian],
CADeTT: Context-Adaptive Deep-Trinary-Tree Lossless Compression of
Event Camera Frames,
SPLetters(31), 2024, pp. 3149-3153.
IEEE DOI
2411
Context modeling, Symbols, Encoding, Computational modeling,
Data models, Probability distribution, Image coding, Cameras, event camera
BibRef
Wang, L.[Lin],
Kim, T.K.[Tae-Kyun],
Yoon, K.J.[Kuk-Jin],
Joint Framework for Single Image Reconstruction and Super-Resolution
With an Event Camera,
PAMI(44), No. 11, November 2022, pp. 7657-7673.
IEEE DOI
2210
Image reconstruction, Superresolution, Spatial resolution,
Streaming media, Task analysis, Training, Event-based vision,
adversarial learning
BibRef
Uddin, S.M.N.[S. M. Nadim],
Ahmed, S.H.[Soikat Hasan],
Jung, Y.J.[Yong Ju],
Unsupervised Deep Event Stereo for Depth Estimation,
CirSysVideo(32), No. 11, November 2022, pp. 7489-7504.
IEEE DOI
2211
Cameras, Estimation, Image matching, Correlation, Training, Lighting,
Image reconstruction, Event camera, stereo matching,
unsupervised deep learning
BibRef
Guo, S.[Shasha],
Delbruck, T.[Tobi],
Low Cost and Latency Event Camera Background Activity Denoising,
PAMI(45), No. 1, January 2023, pp. 785-795.
IEEE DOI
2212
Voltage control, Noise reduction, Cameras, Automobiles,
Noise measurement, Brightness, Vision sensors, ROC
BibRef
Deng, Y.J.[Yong-Jian],
Chen, H.[Hao],
Li, Y.F.[You-Fu],
MVF-Net: A Multi-View Fusion Network for Event-Based Object
Classification,
CirSysVideo(32), No. 12, December 2022, pp. 8275-8284.
IEEE DOI
2212
Cameras, Task analysis, Feature extraction, Data models,
Streaming media, Power demand, Event data, multi-view, attention,
object categorization
BibRef
Baldwin, R.W.[R. Wes],
Liu, R.X.[Rui-Xu],
Almatrafi, M.[Mohammed],
Asari, V.[Vijayan],
Hirakawa, K.[Keigo],
Time-Ordered Recent Event (TORE) Volumes for Event Cameras,
PAMI(45), No. 2, February 2023, pp. 2519-2532.
IEEE DOI
2301
Cameras, Voltage control, Retina, Timing,
Task analysis, Noise reduction, Dynamic vision sensor, denoising
BibRef
Chen, Z.W.[Zhi-Wen],
Wu, J.J.[Jin-Jian],
Hou, J.H.[Jun-Hui],
Li, L.[Leida],
Dong, W.S.[Wei-Sheng],
Shi, G.M.[Guang-Ming],
ECSNet: Spatio-Temporal Feature Learning for Event Camera,
CirSysVideo(33), No. 2, February 2023, pp. 701-712.
IEEE DOI
2302
Feature extraction, Cameras, Task analysis, Cloud computing,
Representation learning, Data mining, Brightness, Event camera,
action recognition
BibRef
Jia, Z.X.[Ze-Xi],
You, K.[Kaichao],
He, W.H.[Wei-Hua],
Tian, Y.[Yang],
Feng, Y.X.[Yong-Xiang],
Wang, Y.[Yaoyuan],
Jia, X.[Xu],
Lou, Y.H.[Yi-Hang],
Zhang, J.Y.[Jing-Yi],
Li, G.Q.[Guo-Qi],
Zhang, Z.Y.[Zi-Yang],
Event-Based Semantic Segmentation With Posterior Attention,
IP(32), 2023, pp. 1829-1842.
IEEE DOI
2303
Cameras, Semantic segmentation, Transformers, Task analysis,
Semantics, Standards, Image segmentation, event camera, attention mechanism
BibRef
Su, Z.[Zhuo],
Zhang, J.[Jiehua],
Wang, L.G.[Long-Guang],
Zhang, H.[Hua],
Liu, Z.[Zhen],
Pietikäinen, M.[Matti],
Liu, L.[Li],
Lightweight Pixel Difference Networks for Efficient Visual
Representation Learning,
PAMI(45), No. 12, December 2023, pp. 14956-14974.
IEEE DOI
2311
BibRef
Chen, H.Y.[Hao-Yu],
Teng, M.G.[Ming-Gui],
Shi, B.X.[Bo-Xin],
Wang, Y.Z.[Yi-Zhou],
Huang, T.J.[Tie-Jun],
A Residual Learning Approach to Deblur and Generate High Frame Rate
Video With an Event Camera,
MultMed(25), 2023, pp. 5826-5839.
IEEE DOI
2311
BibRef
Wang, Z.W.[Zi-Wei],
Ng, Y.[Yonhon],
Scheerlinck, C.[Cedric],
Mahony, R.[Robert],
An Asynchronous Linear Filter Architecture for Hybrid Event-Frame
Cameras,
PAMI(46), No. 2, February 2024, pp. 695-711.
IEEE DOI
2401
BibRef
Earlier:
An Asynchronous Kalman Filter for Hybrid Event Cameras,
ICCV21(438-447)
IEEE DOI
2203
Visualization, Uncertainty, Pipelines, Lighting, Dynamic range,
Sensor fusion, Cameras, Vision + other modalities,
BibRef
Ding, S.[Saizhe],
Chen, J.Z.[Jin-Ze],
Wang, Y.[Yang],
Kang, Y.[Yu],
Song, W.G.[Wei-Guo],
Cheng, J.[Jie],
Cao, Y.[Yang],
E-MLB: Multilevel Benchmark for Event-Based Camera Denoising,
MultMed(26), 2024, pp. 65-76.
IEEE DOI Code:
WWW Link.
2401
BibRef
Ercan, B.[Burak],
Eker, O.[Onur],
Saglam, C.[Canberk],
Erdem, A.[Aykut],
Erdem, E.[Erkut],
HyperE2VID: Improving Event-Based Video Reconstruction via
Hypernetworks,
IP(33), 2024, pp. 1826-1837.
IEEE DOI
2403
Image reconstruction, Task analysis,
Cameras, Optical flow, Image quality, Adaptive filters, dynamic convolutions
BibRef
Chen, W.[Wu],
Zhang, Y.[Yueyi],
Sun, X.Y.[Xiao-Yan],
Wu, F.[Feng],
Event-Based Stereo Depth Estimation by Temporal-Spatial Context
Learning,
SPLetters(31), 2024, pp. 1429-1433.
IEEE DOI
2405
Feature extraction, Estimation, Convolution, Cameras, Data mining,
Context modeling, Event cameras, temporal context
BibRef
Shi, C.Y.[Chen-Yang],
Li, Y.Z.[Yu-Zhen],
Song, N.[Ningfang],
Wei, B.[Boyi],
Zhang, Y.[Yibo],
Li, W.Z.[Wen-Zhuo],
Jin, J.[Jing],
Identifying Light Interference in Event-Based Vision,
CirSysVideo(34), No. 6, June 2024, pp. 4800-4816.
IEEE DOI Code:
WWW Link.
2406
Cameras, Interference, Light sources, Task analysis, Brightness,
Object detection, Reflection, Event-based vision
BibRef
Li, M.J.[Meng-Jie],
Huang, Y.J.[Yu-Jie],
Wang, M.Y.[Ming-Yu],
Li, W.H.[Wen-Hong],
Zeng, X.Y.[Xiao-Yang],
STCC-Filter: A space-time-content correlation-based noise filter with
self-adjusting threshold for event camera,
SP:IC(126), 2024, pp. 117136.
Elsevier DOI
2406
Event camera, Noise filter, Self-adjusting threshold,
Spatiotemporal correlation, Content correlation
BibRef
Salah, M.[Mohammed],
Ayyad, A.[Abdulla],
Humais, M.[Muhammad],
Gehrig, D.[Daniel],
Abusafieh, A.[Abdelqader],
Seneviratne, L.[Lakmal],
Scaramuzza, D.[Davide],
Zweiri, Y.[Yahya],
E-Calib: A Fast, Robust, and Accurate Calibration Toolbox for Event
Cameras,
IP(33), 2024, pp. 3977-3990.
IEEE DOI
2407
Calibration, Cameras, Accuracy, Robustness, Feature extraction, Noise,
Spatiotemporal phenomena, Event-based vision,
feature extraction
BibRef
Zhan, Q.G.[Qiu-Gang],
Liu, G.S.[Gui-Song],
Xie, X.R.[Xiu-Rui],
Tao, R.[Ran],
Zhang, M.[Malu],
Tang, H.J.[Hua-Jin],
Spiking Transfer Learning From RGB Image to Neuromorphic Event Stream,
IP(33), 2024, pp. 4274-4287.
IEEE DOI
2408
Transfer learning, Cameras, Streaming media, Data models, Training,
Loss measurement, Brightness, Spiking neural networks, event camera
BibRef
Guo, Y.F.[Yu-Fei],
Peng, W.[Weihang],
Chen, Y.P.[Yuan-Pei],
Zhou, J.[Jie],
Ma, Z.[Zhe],
Improved Event-Based Image De-Occlusion,
SPLetters(31), 2024, pp. 1930-1934.
IEEE DOI
2408
Decoding, Feature extraction, Membrane potentials, Training data,
Cameras, Task analysis, Streams, Event camera, image de-occlusion,
synthetic aperture imaging
BibRef
Gu, D.X.[Da-Xin],
Li, J.[Jia],
Zhu, L.[Lin],
Learning Adaptive Parameter Representation for Event-Based Video
Reconstruction,
SPLetters(31), 2024, pp. 1950-1954.
IEEE DOI
2408
Image reconstruction, Transformers, Decoding, Streams,
Feature extraction, Training, Spatiotemporal phenomena,
contrast threshold
BibRef
Annamalai, L.[Lakshmi],
Thakur, C.S.[Chetan Singh],
Beyond supervision: An unsupervised spatio-temporal point cloud noise
modeling for event vision sensor,
PRL(184), 2024, pp. 162-168.
Elsevier DOI
2408
Noise modeling, Mixture model, Event camera
BibRef
Qu, Q.[Qiang],
Chen, X.M.[Xiao-Ming],
Chung, Y.Y.[Yuk Ying],
Shen, Y.[Yiran],
EvRepSL: Event-Stream Representation via Self-Supervised Learning for
Event-Based Vision,
IP(33), 2024, pp. 6579-6591.
IEEE DOI
2412
Cameras, Event detection, Optical flow, Estimation,
Self-supervised learning, Noise, Accuracy, Generators, event-based vision
BibRef
Yang, C.[Chen],
Li, G.R.[Guo-Rong],
Wang, S.H.[Shu-Hui],
Su, L.[Li],
Qing, L.Y.[Lai-Yun],
Huang, Q.M.[Qing-Ming],
SpikeODE: Image Reconstruction for Spike Camera With Neural Ordinary
Differential Equation,
CirSysVideo(34), No. 11, November 2024, pp. 11142-11155.
IEEE DOI
2412
Cameras, Image reconstruction, Correlation, Image restoration, Noise,
Task analysis, Streaming media, Spike camera, image reconstruction,
temporal-spatial correlation
BibRef
Chen, Z.W.[Zhi-Wen],
Wu, J.J.[Jin-Jian],
Dong, W.S.[Wei-Sheng],
Li, L.[Leida],
Shi, G.M.[Guang-Ming],
CrossEI: Boosting Motion-Oriented Object Tracking With an Event
Camera,
IP(34), 2025, pp. 73-84.
IEEE DOI
2501
Tracking, Cameras, Feature extraction, Semantics, Object tracking,
Motion estimation, Modulation, Dynamics, Sensitivity
BibRef
Xie, B.[Bochen],
Deng, Y.J.[Yong-Jian],
Shao, Z.P.[Zhan-Peng],
Xu, Q.S.[Qing-Song],
Li, Y.F.[You-Fu],
Event Voxel Set Transformer for Spatiotemporal Representation
Learning on Event Streams,
CirSysVideo(34), No. 12, December 2024, pp. 13427-13440.
IEEE DOI
2501
Streams, Cameras, Transformers, Task analysis,
Spatiotemporal phenomena, Feature extraction,
action recognition
BibRef
Lin, S.N.[Song-Nan],
Ma, Y.[Ye],
Chen, J.[Jing],
Wen, B.H.[Bi-Han],
Compressed Event Sensing (CES) Volumes for Event Cameras,
IJCV(133), No. 1, January 2025, pp. 435-455.
Springer DOI
2501
BibRef
Lin, S.N.[Song-Nan],
Ma, Y.[Ye],
Guo, Z.H.[Zhen-Hua],
Wen, B.H.[Bi-Han],
DVS-Voltmeter:
Stochastic Process-Based Event Simulator for Dynamic Vision Sensors,
ECCV22(VII:578-593).
Springer DOI
2211
BibRef
Zhu, L.[Lin],
Chen, X.Z.[Xian-Zhang],
Wang, L.Z.[Li-Zhi],
Wang, X.[Xiao],
Tian, Y.H.[Yong-Hong],
Huang, H.[Hua],
Continuous-Time Object Segmentation Using High Temporal Resolution
Event Camera,
PAMI(47), No. 2, February 2025, pp. 807-824.
IEEE DOI
2501
Streams, Object segmentation, Feature extraction, Cameras,
Motion segmentation, Spatiotemporal phenomena,
temporal information extraction
BibRef
Zhang, P.[Pei],
Zhu, S.[Shuo],
Wang, C.[Chutian],
Zhao, Y.P.[Ya-Ping],
Lam, E.Y.[Edmund Y.],
Neuromorphic Imaging With Super-Resolution,
CirSysVideo(35), No. 2, February 2025, pp. 1715-1727.
IEEE DOI
2502
Imitates the human retina to sense variations in dynamic scenes.
Neuromorphics, Cameras, Spatial resolution, Training,
Superresolution, Streaming media, Visualization
BibRef
Ge, C.J.[Cheng-Jie],
Fu, X.Y.[Xue-Yang],
Wang, K.Y.[Kun-Yu],
Zha, Z.J.[Zheng-Jun],
Event-Based Video Reconstruction With Deep Spatial-Frequency
Unfolding Network,
IP(34), 2025, pp. 1779-1794.
IEEE DOI
2503
Image reconstruction, Event detection, Frequency-domain analysis,
Brightness, Cameras, Computational modeling, Transformers,
spatial-frequency network
BibRef
Alim, D.[Dilmurat],
Yang, C.[Chen],
Qing, L.Y.[Lai-Yun],
Li, G.R.[Guo-Rong],
Huang, Q.M.[Qing-Ming],
MMA: Video Reconstruction for Spike Camera Based on Multiscale
Temporal Modeling and Fine-Grained Attention,
SPLetters(32), 2025, pp. 1291-1295.
IEEE DOI
2504
Image reconstruction, Feature extraction, Streaming media,
Computational modeling, Decoding, Cameras, Training, Image quality,
Mamba
BibRef
Messikommer, N.[Nico],
Fang, C.[Carter],
Gehrig, M.[Mathias],
Cioffi, G.[Giovanni],
Scaramuzza, D.[Davide],
Data-Driven Feature Tracking for Event Cameras With and Without
Frames,
PAMI(47), No. 5, May 2025, pp. 3706-3717.
IEEE DOI
2504
BibRef
Earlier: A1, A2, A3, A5, Only:
Data-Driven Feature Tracking for Event Cameras,
CVPR23(5642-5651)
IEEE DOI
2309
WWW Link. Cameras, Feature extraction, Estimation, Tracking, Standards, Streams,
Event detection, Optical flow,
sparse disparity estimation
BibRef
Shi, C.Y.[Chen-Yang],
Wei, B.[Boyi],
Wang, X.C.[Xiu-Cheng],
Liu, H.X.[Han-Xiao],
Zhang, Y.[Yibo],
Li, W.Z.[Wen-Zhuo],
Song, N.F.[Ning-Fang],
Jin, J.[Jing],
Polarity-Focused Denoising for Event Cameras,
CirSysVideo(35), No. 5, May 2025, pp. 4370-4383.
IEEE DOI Code:
WWW Link.
2505
Noise reduction, Noise, Cameras, Spatiotemporal phenomena,
Phase frequency detectors, Real-time systems, flicker noise
BibRef
Feng, K.[Kexiang],
Jia, C.M.[Chuan-Min],
Pan, J.S.[Jing-Shan],
Ma, S.W.[Si-Wei],
Gao, W.[Wen],
End-to-End Optimized Lossy Compression for Neural-Morphic Spiking
Camera Captured Data,
CirSysVideo(35), No. 6, June 2025, pp. 6074-6086.
IEEE DOI
2506
Image coding, Cameras, Image reconstruction, Streams, Correlation, Redundancy,
Visualization, Firing, Spatial resolution, Retina, end-to-end spike coding
BibRef
Yi, Z.H.[Zhong-Hua],
Sh, H.[Hao],
Jiang, Q.[Qi],
Yang, K.L.[Kai-Lun],
Wang, Z.[Ze],
Gu, D.[Diyang],
Zhang, Y.F.[Yu-Fan],
Wang, K.W.[Kai-Wei],
EI-Nexus: Towards Unmediated and Flexible Inter-Modality Local
Feature Extraction and Matching for Event-Image Data,
WACV25(1979-1988)
IEEE DOI
2505
Location awareness, Visualization,
Simultaneous localization and mapping, Source coding,
inter-modality feature extraction
BibRef
Karmokar, P.P.[Pritam P.],
Nguyen, Q.H.[Quan H.],
Beksi, W.J.[William J.],
Secrets of Edge-Informed Contrast Maximization for Event-Based Vision,
WACV25(630-639)
IEEE DOI
2505
Training, Accuracy, Image edge detection, Benchmark testing, Cameras,
Trajectory, Reliability, Noise measurement, Optical flow, Optimization
BibRef
Saghand, E.G.[Esmat Ghasemi],
Lai-Yuen, S.K.[Susana K.],
MONAS-ESNN: Multi-Objective Neural Architecture Search for Efficient
Spiking Neural Networks,
WACV25(2963-2972)
IEEE DOI
2505
Training, Measurement, Accuracy, Neurons,
Spiking neural networks, Linear programming, Energy efficiency,
image classification
BibRef
Yin, J.Y.[Jiao-Yang],
Fan, B.[Bin],
Xu, C.[Chao],
Huang, T.J.[Tie-Jun],
Shi, B.X.[Bo-Xin],
Spk2ImgMamba: Spiking Camera Image Reconstruction with Multi-Scale
State Space Models,
WACV25(9342-9352)
IEEE DOI Code:
WWW Link.
2505
Correlation, Computational modeling, Reconstruction algorithms,
Vision sensors, Transformer cores, Streaming media, Cameras, MAMBA
BibRef
Santambrogio, R.[Riccardo],
Cannici, M.[Marco],
Matteucci, M.[Matteo],
FARSE-CNN: Fully Asynchronous, Recurrent and Sparse Event-based Cnn,
ECCV24(LIV: 1-18).
Springer DOI
2412
Code:
WWW Link.
BibRef
Ren, Z.Y.[Zhong-Yang],
Liao, B.Y.[Bang-Yan],
Kong, D.[Delei],
Li, J.H.[Jing-Hang],
Liu, P.[Peidong],
Kneip, L.[Laurent],
Gallego, G.[Guillermo],
Zhou, Y.[Yi],
Motion and Structure from Event-based Normal Flow,
ECCV24(LVI: 108-125).
Springer DOI
2412
BibRef
Kamal, U.[Uday],
Mukhopadhyay, S.[Saibal],
Efficient Learning of Event-based Dense Representation Using
Hierarchical Memories with Adaptive Update,
ECCV24(LXXXII: 74-89).
Springer DOI
2412
BibRef
Guo, Q.[Qi],
Shi, H.L.[Hai-Long],
Li, H.[Huan],
Xiao, J.S.[Jin-Sheng],
Gao, X.Y.[Xing-Yu],
Redir: Refocus-free Event-based De-occlusion Image Reconstruction,
ECCV24(LXXX: 419-435).
Springer DOI
2412
BibRef
Han, H.Q.[Hai-Qian],
Lyu, J.C.[Jia-Cheng],
Li, J.N.[Jia-Ning],
Wei, H.[Henglu],
Li, C.[Cheng],
Wei, Y.J.[Ya-Jing],
Chen, S.[Shu],
Ji, X.Y.[Xiang-Yang],
Physical-based Event Camera Simulator,
ECCV24(XLV: 19-35).
Springer DOI
2412
BibRef
Bao, Y.H.[Yu-Han],
Sun, L.[Lei],
Ma, Y.Q.[Yu-Qin],
Wang, K.W.[Kai-Wei],
Temporal-mapping Photography for Event Cameras,
ECCV24(LV: 55-72).
Springer DOI
2412
BibRef
Wang, Z.P.[Zi-Peng],
Lu, Y.F.[Yun-Fan],
Wang, L.[Lin],
Revisit Event Generation Model: Self-supervised Learning of
Event-to-video Reconstruction with Implicit Neural Representations,
ECCV24(XLIX: 321-339).
Springer DOI
2412
BibRef
Yu, J.Z.[Jin-Ze],
Peng, X.[Xin],
Lu, Z.[Zhengda],
Kneip, L.[Laurent],
Wang, Y.Q.[Yi-Qun],
Spikegs: Learning 3d Gaussian Fields from Continuous Spike Stream,
ACCV24(X: 159-177).
Springer DOI
2412
BibRef
Zhao, F.[Fengan],
Zhou, Q.[Qianang],
Xiong, J.L.[Jun-Lin],
Edge-Guided Fusion and Motion Augmentation for Event-image Stereo,
ECCV24(LXXIII: 190-205).
Springer DOI
2412
BibRef
Tang, J.X.[Jian-Xiong],
Lai, J.H.[Jian-Huang],
Yang, L.X.[Ling-Xiao],
Xie, X.H.[Xiao-Hua],
Spike-temporal Latent Representation for Energy-efficient
Event-to-video Reconstruction,
ECCV24(XLII: 163-179).
Springer DOI
2412
BibRef
Henry, C.[Chris],
Maharjan, P.[Paras],
Li, Z.[Zhu],
York, G.[George],
E2SIFT: Neuromorphic SIFT via Direct Feature Pyramid Recovery from
Events,
ICIP24(2786-2792)
IEEE DOI
2411
Thresholding (Imaging), Neuromorphics, Detectors, Transforms,
Streaming media, Vision sensors, Cameras,
keypoint detection
BibRef
Wang, Y.L.[Yuan-Lin],
Xiong, R.Q.[Rui-Qin],
Zhao, J.[Jing],
Huang, T.J.[Tie-Jun],
Reconstruct Dynamic Scene for Spike Camera Based on 3D Space Time
Similarity,
ICIP24(1595-1601)
IEEE DOI
2411
Visualization, Correlation, Quantization (signal), Estimation,
Reconstruction algorithms, Cameras, spike camera,
high-speed photography
BibRef
Ramon, R.[Raz],
Cohen-Duwek, H.[Hadar],
Tsur, E.E.[Elishai Ezra],
ED-DCFNet: an unsupervised encoder-decoder neural model for
event-driven feature extraction and object tracking,
ECVW24(2191-2199)
IEEE DOI Code:
WWW Link.
2410
Training, Neuromorphics, Computational modeling, Machine vision,
Supervised learning, Feature extraction, object tracking
BibRef
Li, S.Q.[Si-Qi],
Zhou, Z.[Zhikuan],
Xue, Z.[Zhou],
Li, Y.P.[Yi-Peng],
Du, S.[Shaoyi],
Gao, Y.[Yue],
3D Feature Tracking via Event Camera,
CVPR24(18974-18983)
IEEE DOI Code:
WWW Link.
2410
Target tracking, Tracking, Deformation, Benchmark testing, Cameras,
Motion compensation, Event Camera, Feature Tracking, 3D Vision, Dataset
BibRef
Elms, E.[Ethan],
Latif, Y.[Yasir],
Park, T.H.[Tae Ha],
Chin, T.J.[Tat-Jun],
Event-based Structure-from-Orbit,
CVPR24(19541-19550)
IEEE DOI
2410
Visualization, Tracking, Sparse approximation,
Robot vision systems, Cameras, Orbits, Event camera, Dataset
BibRef
Zheng, X.[Xu],
Wang, L.[Lin],
EventDance: Unsupervised Source-Free Cross-Modal Adaptation for
Event-Based Object Recognition,
CVPR24(17448-17458)
IEEE DOI
2410
Adaptation models, Data privacy, Image edge detection,
Reconstruction algorithms, Data models, Spatiotemporal phenomena
BibRef
Wu, Z.[Ziyi],
Gehrig, M.[Mathias],
Lyu, Q.[Qing],
Liu, X.D.[Xu-Dong],
Gilitschenski, I.[Igor],
LEOD: Label-Efficient Object Detection for Event Cameras,
CVPR24(16933-16942)
IEEE DOI Code:
WWW Link.
2410
Training, Protocols, Noise, Object detection, Detectors, Cameras,
Event-based Vision, Object Detection,
Weakly-supervised Learning
BibRef
Sundar, V.[Varun],
Dutson, M.[Matthew],
Ardelean, A.[Andrei],
Bruschini, C.[Claudio],
Charbon, E.[Edoardo],
Gupta, M.[Mohit],
Generalized Event Cameras,
CVPR24(25007-25017)
IEEE DOI
2410
Costs, Computational modeling, Brightness, Bandwidth, Cameras, Sensors,
Event cameras, computational imaging, single-photon imaging
BibRef
Shah, S.[Sachin],
Chan, M.A.[Matthew A.],
Cai, H.M.[Hao-Ming],
Chen, J.X.[Jing-Xi],
Kulshrestha, S.[Sakshum],
Singh, C.D.[Chahat Deep],
Aloimonos, Y.F.[Yi-Fannis],
Metzler, C.A.[Christopher A.],
CodedEvents: Optimal Point-Spread-Function Engineering for
3D-Tracking with Event Cameras,
CVPR24(25265-25275)
IEEE DOI
2410
Location awareness, Neuromorphics, Prototypes, Fluorescence, Cameras,
Optical imaging, Computational Imaging, Event Cameras, Coded Aperture
BibRef
Gao, Y.[Yuan],
Zhu, Y.Q.[Yu-Qing],
Li, X.J.[Xin-Jun],
Du, Y.M.[Yi-Min],
Zhang, T.Z.[Tian-Zhu],
SD2Event: Self-Supervised Learning of Dynamic Detectors and Contextual
Descriptors for Event Cameras,
CVPR24(3055-3064)
IEEE DOI
2410
Adaptation models, Noise, Detectors, Benchmark testing, Cameras,
Feature extraction
BibRef
Zubic, N.[Nikola],
Gehrig, M.[Mathias],
Scaramuzza, D.[Davide],
State Space Models for Event Cameras,
CVPR24(5819-5828)
IEEE DOI
2410
Training, Adaptation models, Time-frequency analysis, Visualization,
Technological innovation, Benchmark testing, event cameras
BibRef
Peng, Y.S.[Yan-Song],
Li, H.[Hebei],
Zhang, Y.[Yueyi],
Sun, X.Y.[Xiao-Yan],
Wu, F.[Feng],
Scene Adaptive Sparse Transformer for Event-based Object Detection,
CVPR24(16794-16804)
IEEE DOI Code:
WWW Link.
2410
Fault tolerance, Power demand, Costs, Fault tolerant systems,
Object detection, Transformers
BibRef
Duan, Y.X.[Yu-Xing],
LED: A Large-scale Real-world Paired Dataset for Event Camera
Denoising,
CVPR24(25637-25647)
IEEE DOI Code:
WWW Link.
2410
Noise reduction, Noise, Neurons, Lighting, Light emitting diodes, Cameras
BibRef
Klenk, S.[Simon],
Bonello, D.[David],
Koestler, L.[Lukas],
Araslanov, N.[Nikita],
Cremers, D.[Daniel],
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras,
WACV24(2367-2377)
IEEE DOI
2404
Micromechanical devices, Semantic segmentation, Semantics,
Training data, Self-supervised learning, Cameras, Data models,
Image recognition and understanding
BibRef
Fox, G.[Gereon],
Pan, X.G.[Xin-Gang],
Tewari, A.[Ayush],
Elgharib, M.[Mohamed],
Theobalt, C.[Christian],
Unsupervised Event-Based Video Reconstruction,
WACV24(4167-4176)
IEEE DOI
2404
Training, Interpolation, Uncertainty, Brightness, Noise, Semantics,
Neural networks, Algorithms, Computational photography,
image and video synthesis
BibRef
Biswas, S.D.[Shristi Das],
Kosta, A.[Adarsh],
Liyanagedera, C.[Chamika],
Apolinario, M.[Marco],
Roy, K.[Kaushik],
HALSIE: Hybrid Approach to Learning Segmentation by Simultaneously
Exploiting Image and Event Modalities,
WACV24(5952-5962)
IEEE DOI
2404
Visualization, Costs, Semantic segmentation, Semantics,
Feature extraction, Cameras, Task analysis, Applications,
Smartphones / end user devices
BibRef
Peng, Y.S.[Yan-Song],
Zhang, Y.[Yueyi],
Xiong, Z.W.[Zhi-Wei],
Sun, X.Y.[Xiao-Yan],
Wu, F.[Feng],
GET: Group Event Transformer for Event-Based Vision,
ICCV23(6015-6025)
IEEE DOI Code:
WWW Link.
2401
BibRef
Zubic, N.[Nikola],
Gehrig, D.[Daniel],
Gehrig, M.[Mathias],
Scaramuzza, D.[Davide],
From Chaos Comes Order: Ordering Event Representations for Object
Recognition and Detection,
ICCV23(12800-12810)
IEEE DOI
2401
BibRef
Cho, H.[Hoonhee],
Kang, J.Y.[Jae-Young],
Yoon, K.J.[Kuk-Jin],
Temporal Event Stereo via Joint Learning with Stereoscopic Flow,
ECCV24(XXXV: 294-314).
Springer DOI
2412
BibRef
Cho, H.[Hoonhee],
Kim, H.[Hyeonseong],
Chae, Y.[Yujeong],
Yoon, K.J.[Kuk-Jin],
Label-Free Event-based Object Recognition via Joint Learning with
Image Reconstruction from Events,
ICCV23(19809-19820)
IEEE DOI Code:
WWW Link.
2401
BibRef
Zhu, Z.Y.[Zhi-Yu],
Hou, J.H.[Jun-Hui],
Wu, D.P.O.[Da-Peng Oliver],
Cross-Modal Orthogonal High-Rank Augmentation for RGB-Event
Transformer-trackers,
ICCV23(21988-21998)
IEEE DOI Code:
WWW Link.
2401
BibRef
Nunes, U.M.[Urbano Miguel],
Perrinet, L.U.[Laurent Udo],
Ieng, S.H.[Sio-Hoi],
Time-to-Contact Map by Joint Estimation of Up-to-Scale Inverse Depth
and Global Motion using a Single Event Camera,
ICCV23(23596-23606)
IEEE DOI
2401
BibRef
Gao, L.[Ling],
Su, H.[Hang],
Gehrig, D.[Daniel],
Cannici, M.[Marco],
Scaramuzza, D.[Davide],
Kneip, L.[Laurent],
A 5-Point Minimal Solver for Event Camera Relative Motion Estimation,
ICCV23(8015-8025)
IEEE DOI
2401
BibRef
Yang, Y.[Yan],
Pan, L.Y.[Li-Yuan],
Liu, L.[Liu],
Event Camera Data Dense Pre-training,
ECCV24(XLIII: 292-310).
Springer DOI
2412
BibRef
Earlier:
Event Camera Data Pre-training,
ICCV23(10665-10675)
IEEE DOI Code:
WWW Link.
2401
BibRef
Tsuji, Y.[Yuta],
Yatagawa, T.[Tatsuya],
Kubo, H.[Hiroyuki],
Morishima, S.[Shigeo],
Event-Based Camera Simulation Using Monte Carlo Path Tracing with
Adaptive Denoising,
ICIP23(301-305)
IEEE DOI Code:
WWW Link.
2312
BibRef
Gehrig, M.[Mathias],
Scaramuzza, D.[Davide],
Recurrent Vision Transformers for Object Detection with Event Cameras,
CVPR23(13884-13893)
IEEE DOI
2309
WWW Link.
BibRef
Hamaguchi, R.[Ryuhei],
Furukawa, Y.[Yasutaka],
Onishi, M.[Masaki],
Sakurada, K.[Ken],
Hierarchical Neural Memory Network for Low Latency Event Processing,
CVPR23(22867-22876)
IEEE DOI
2309
BibRef
Xu, L.X.[Le-Xuan],
Hua, G.[Guang],
Zhang, H.J.[Hai-Jian],
Yu, L.[Lei],
Qiao, N.[Ning],
'Seeing' Electric Network Frequency from Events,
CVPR23(18022-18031)
IEEE DOI
2309
WWW Link. Extract grid frequency via event camera.
BibRef
Cho, H.[Hoonhee],
Cho, J.[Jegyeong],
Yoon, K.J.[Kuk-Jin],
Learning Adaptive Dense Event Stereo from the Image Domain,
CVPR23(17797-17807)
IEEE DOI
2309
BibRef
Cadena, P.R.G.[Pablo Rodrigo Gantier],
Qian, Y.Q.[Ye-Qiang],
Wang, C.X.[Chun-Xiang],
Yang, M.[Ming],
Sparse-E2VID: A Sparse Convolutional Model for Event-Based Video
Reconstruction Trained with Real Event Noise,
EventVision23(4150-4158)
IEEE DOI
2309
BibRef
Kowalczyk, M.[Marcin],
Kryjak, T.[Tomasz],
Interpolation-Based Event Visual Data Filtering Algorithms,
EventVision23(4056-4064)
IEEE DOI
2309
BibRef
Im, G.[Gyubeom],
Park, K.[Keunjoo],
Kim, J.[Junseok],
Son, B.[Bongki],
Shin, S.C.[Seung-Chul],
Lee, H.[Haechang],
Live Demonstration: PINK: Polarity-based Anti-flicker for Event
Cameras,
EventVision23(3901-3902)
IEEE DOI
2309
BibRef
Kugele, A.[Alexander],
Pfeil, T.[Thomas],
Pfeiffer, M.[Michael],
Chicca, E.[Elisabetta],
How Many Events Make an Object? Improving Single-frame Object
Detection on the 1 Mpx Dataset,
EventVision23(3913-3922)
IEEE DOI
2309
BibRef
Schiopu, I.[Ionut],
Bilcu, R.C.[Radu Ciprian],
Entropy Coding-based Lossless Compression of Asynchronous Event
Sequences,
EventVision23(3923-3930)
IEEE DOI
2309
BibRef
Rios-Navarro, A.,
Guo, S.,
Abarajithan, G.,
Vijayakumar, K.,
Linares-Barranco, A.,
Aarrestad, T.,
Kastner, R.,
Delbruck, T.,
Within-Camera Multilayer Perceptron DVS Denoising,
EventVision23(3933-3942)
IEEE DOI
2309
BibRef
Ercan, B.[Burak],
Eker, O.[Onur],
Erdem, A.[Aykut],
Erdem, E.[Erkut],
EVREAL: Towards a Comprehensive Benchmark and Analysis Suite for
Event-based Video Reconstruction,
EventVision23(3943-3952)
IEEE DOI
2309
BibRef
Chamorro, W.[William],
Solŕ, J.[Joan],
Andrade-Cetto, J.[Juan],
Event-IMU fusion strategies for faster-than-IMU estimation throughput,
EventVision23(3976-3983)
IEEE DOI
2309
BibRef
Bose, L.[Laurie],
Dudek, P.[Piotr],
Carey, S.J.[Stephen J.],
Chen, J.N.[Jia-Ning],
Live Demonstration: SCAMP-7,
EventVision23(3995-3996)
IEEE DOI
2309
BibRef
Graça, R.[Rui],
McReynolds, B.[Brian],
Delbruck, T.[Tobi],
Shining light on the DVS pixel: A tutorial and discussion about
biasing and optimization,
EventVision23(4045-4053)
IEEE DOI
2309
BibRef
Niwa, R.[Ryogo],
Fushimi, T.[Tatsuki],
Yamamoto, K.[Kenta],
Ochiai, Y.[Yoichi],
Live Demonstration: Event-based Visual Microphone,
EventVision23(4054-4055)
IEEE DOI
2309
BibRef
Huang, X.Y.[Xue-Yan],
Zhang, Y.[Yueyi],
Xiong, Z.W.[Zhi-Wei],
Progressive Spatio-temporal Alignment for Efficient Event-based
Motion Estimation,
CVPR23(1537-1546)
IEEE DOI
2309
WWW Link.
BibRef
Gruel, A.[Amélie],
Carreras, L.T.[Lucía Trillo],
García, M.B.[Marina Bueno],
Kupczyk, E.[Ewa],
Martinet, J.[Jean],
Frugal event data: how small is too small? A human performance
assessment with shrinking data,
EventVision23(4093-4100)
IEEE DOI
2309
BibRef
Muglikar, M.[Manasi],
Bauersfeld, L.[Leonard],
Moeys, D.P.[Diederik Paul],
Scaramuzza, D.[Davide],
Event-Based Shape from Polarization,
CVPR23(1547-1556)
IEEE DOI
2309
WWW Link.
BibRef
Barchid, S.[Sami],
Mennesson, J.[José],
Djéraba, C.[Chaabane],
Exploring Joint Embedding Architectures and Data Augmentations for
Self-Supervised Representation Learning in Event-Based Vision,
EventVision23(3903-3912)
IEEE DOI
2309
BibRef
Haessig, G.[Germain],
Joubert, D.[Damien],
Haque, J.[Justin],
Milde, M.B.[Moritz B.],
Delbruck, T.[Tobi],
Gruev, V.[Viktor],
PDAVIS: Bio-inspired Polarization Event Camera,
EventVision23(3963-3972)
IEEE DOI
2309
BibRef
Nunes, U.M.[Urbano Miguel],
Benosman, R.[Ryad],
Ieng, S.H.[Sio-Hoi],
Adaptive Global Decay Process for Event Cameras,
CVPR23(9771-9780)
IEEE DOI
2309
BibRef
Hwang, I.[Inwoo],
Kim, J.[Junho],
Kim, Y.M.[Young Min],
Ev-NeRF: Event Based Neural Radiance Field,
WACV23(837-847)
IEEE DOI
2302
Image sensors, Solid modeling, Volume measurement, Lighting, Cameras,
Loss measurement, Sensors, Algorithms: 3D computer vision,
image and video synthesis
BibRef
Huang, Z.[Ze],
Sun, L.[Li],
Zhao, C.[Cheng],
Li, S.[Song],
Su, S.[Songzhi],
EventPoint: Self-Supervised Interest Point Detection and Description
for Event-based Camera,
WACV23(5385-5394)
IEEE DOI
2302
Knowledge engineering, Representation learning, Power demand,
Annotations, Neural networks, Detectors, Self-supervised learning, Robotics
BibRef
Sun, L.H.[Lin-Hui],
Zhang, Y.F.[Yi-Fan],
Cheng, K.[Ke],
Cheng, J.[Jian],
Lu, H.Q.[Han-Qing],
MENet: A Memory-Based Network with Dual-Branch for Efficient Event
Stream Processing,
ECCV22(XXIV:214-234).
Springer DOI
2211
BibRef
Zhang, D.H.[De-Hao],
Ding, Q.K.[Qian-Kun],
Duan, P.Q.[Pei-Qi],
Zhou, C.[Chu],
Shi, B.X.[Bo-Xin],
Data Association Between Event Streams and Intensity Frames Under
Diverse Baselines,
ECCV22(VII:72-90).
Springer DOI
2211
BibRef
Wan, Z.Y.[Zeng-Yu],
Wang, Y.[Yang],
Tan, G.C.[Gan-Chao],
Cao, Y.[Yang],
Zha, Z.J.[Zheng-Jun],
S2N: Suppression-Strengthen Network for Event-Based Recognition Under
Variant Illuminations,
ECCV22(III:716-733).
Springer DOI
2211
BibRef
Cho, H.[Hoonhee],
Yoon, K.J.[Kuk-Jin],
Selection and Cross Similarity for Event-Image Deep Stereo,
ECCV22(XXXII:470-486).
Springer DOI
2211
BibRef
Barchid, S.[Sami],
Mennesson, J.[José],
Djéraba, C.[Chaabane],
Bina-Rep Event Frames:
A Simple and Effective Representation for Event-Based Cameras,
ICIP22(3998-4002)
IEEE DOI
2211
Sensitivity, Image recognition, Neuromorphics, Streaming media,
Cameras, Robustness, Convolutional neural networks, Event Cameras,
Object Recognition
BibRef
Wang, Z.[Zuowen],
Hu, Y.[Yuhuang],
Liu, S.C.[Shih-Chii],
Exploiting Spatial Sparsity for Event Cameras with Visual
Transformers,
ICIP22(411-415)
IEEE DOI
2211
Visualization, Pipelines, Brightness, Transformers, Cameras,
Event cameras, Spatial sparsity, Reduced computation, Visual transformers
BibRef
Delbruck, T.[Tobi],
Li, C.[Chenghan],
Graca, R.[Rui],
Mcreynolds, B.[Brian],
Utility and Feasibility of a Center Surround Event Camera,
ICIP22(381-385)
IEEE DOI
2211
Resistors, Switches, Vision sensors, Retina, Cameras, Transconductors,
Biology, pixel, neuromorphic
BibRef
Liao, W.[Wei],
Zhang, X.[Xiang],
Yu, L.[Lei],
Lin, S.J.[Shi-Jie],
Yang, W.[Wen],
Qiao, N.[Ning],
Synthetic Aperture Imaging with Events and Frames,
CVPR22(17714-17723)
IEEE DOI
2210
Photography, Visualization, Codes, Lighting, Apertures,
Feature extraction, Computational photography, Low-level vision
BibRef
Kim, J.[Junho],
Hwang, I.[Inwoo],
Kim, Y.M.[Young Min],
Ev-TTA: Test-Time Adaptation for Event-Based Object Recognition,
CVPR22(17724-17733)
IEEE DOI
2210
Training, Lighting, Performance gain, Prediction algorithms, Cameras,
Loss measurement, Classification algorithms,
Transfer/low-shot/long-tail learning
BibRef
Zhang, K.X.[Kai-Xuan],
Che, K.W.[Kai-Wei],
Zhang, J.G.[Jian-Guo],
Cheng, J.[Jie],
Zhang, Z.Y.[Zi-Yang],
Guo, Q.H.[Qing-Hai],
Leng, L.[Luziwei],
Discrete time convolution for fast event-based stereo,
CVPR22(8666-8676)
IEEE DOI
2210
Convolution, Biological system modeling, Computational modeling,
Estimation, Feature extraction, Encoding, Data models, Vision+X
BibRef
Nam, Y.[Yeongwoo],
Mostafavi, M.[Mohammad],
Yoon, K.J.[Kuk-Jin],
Choi, J.H.[Jong-Hyun],
Stereo Depth from Events Cameras: Concentrate and Focus on the Future,
CVPR22(6104-6113)
IEEE DOI
2210
Training, Art, Tensors, Robot vision systems, Estimation,
Streaming media, Low-level vision,
Robot vision
BibRef
Deng, Y.J.[Yong-Jian],
Chen, H.[Hao],
Liu, H.[Hai],
Li, Y.F.[You-Fu],
A Voxel Graph CNN for Object Classification with Event Cameras,
CVPR22(1162-1171)
IEEE DOI
2210
Learning systems, Power demand, Limiting, Computational modeling,
Semantics, Robot vision systems, Cameras, Recognition: detection,
Robot vision
BibRef
He, W.H.[Wei-Hua],
You, K.[Kaichao],
Qiao, Z.D.[Zhen-Dong],
Jia, X.[Xu],
Zhang, Z.Y.[Zi-Yang],
Wang, W.H.[Wen-Hui],
Lu, H.C.[Hu-Chuan],
Wang, Y.Y.[Yao-Yuan],
Liao, J.X.[Jian-Xing],
TimeReplayer: Unlocking the Potential of Event Cameras for Video
Interpolation,
CVPR22(17783-17792)
IEEE DOI
2210
Training, Interpolation, Extrapolation, Costs, Training data, Cameras,
Recording, Computational photography, Low-level vision
BibRef
Han, J.[Jin],
Yang, Y.X.[Yi-Xin],
Zhou, C.[Chu],
Xu, C.[Chao],
Shi, B.X.[Bo-Xin],
EvIntSR-Net: Event Guided Multiple Latent Frames Reconstruction and
Super-resolution,
ICCV21(4862-4871)
IEEE DOI
2203
Bridges, Fuses, Superresolution, Streaming media, Dynamic range,
Cameras, Spatial resolution, Low-level and physics-based vision,
Computational photography
BibRef
Yao, M.[Man],
Gao, H.H.[Huan-Huan],
Zhao, G.S.[Guang-She],
Wang, D.H.[Ding-Heng],
Lin, Y.[Yihan],
Yang, Z.X.[Zhao-Xu],
Li, G.Q.[Guo-Qi],
Temporal-wise Attention Spiking Neural Networks for Event Streams
Classification,
ICCV21(10201-10210)
IEEE DOI
2203
Training, Computational modeling, Gesture recognition,
Streaming media, Feature extraction, Brain modeling, Task analysis,
Recognition and classification
BibRef
Zhang, J.Q.[Ji-Qing],
Yang, X.[Xin],
Fu, Y.[Yingkai],
Wei, X.P.[Xiao-Peng],
Yin, B.C.[Bao-Cai],
Dong, B.[Bo],
Object Tracking by Jointly Exploiting Frame and Event Domain,
ICCV21(13023-13032)
IEEE DOI
2203
Visualization, Adaptation models, Fuses, Dynamic range, Cameras,
Object tracking, Motion and tracking,
BibRef
Li, Y.J.[Yi-Jin],
Zhou, H.[Han],
Yang, B.B.[Bang-Bang],
Zhang, Y.[Ye],
Cui, Z.P.[Zhao-Peng],
Bao, H.J.[Hu-Jun],
Zhang, G.F.[Guo-Feng],
Graph-based Asynchronous Event Processing for Rapid Object
Recognition,
ICCV21(914-923)
IEEE DOI
2203
Convolution, Streaming media, Cameras, Prediction algorithms,
Windows, Object recognition, Computational complexity,
BibRef
Wang, L.[Lin],
Chae, Y.J.[Yu-Jeong],
Yoon, K.J.[Kuk-Jin],
Dual Transfer Learning for Event-based End-task Prediction via
Pluggable Event to Image Translation,
ICCV21(2115-2125)
IEEE DOI
2203
Representation learning, Electrical impedance tomography,
Visualization, Image segmentation, Motion segmentation,
Vision + other modalities
BibRef
Mostafavi, S.I.M.[S.I. Mohammad],
Yoon, K.J.[Kuk-Jin],
Choi, J.H.[Jong-Hyun],
Event-Intensity Stereo: Estimating Depth by the Best of Both Worlds,
ICCV21(4238-4247)
IEEE DOI
2203
Power demand, Computer network reliability, Neural networks,
Estimation, Dynamic range, Benchmark testing,
3D from multiview and other sensors
BibRef
Li, S.Q.[Si-Qi],
Feng, Y.T.[Yu-Tong],
Li, Y.P.[Yi-Peng],
Jiang, Y.[Yu],
Zou, C.Q.[Chang-Qing],
Gao, Y.[Yue],
Event Stream Super-Resolution via Spatiotemporal Constraint Learning,
ICCV21(4460-4469)
IEEE DOI
2203
Learning systems, Superresolution, Neural networks,
Streaming media, Cameras, Real-time systems,
BibRef
Gu, C.[Cheng],
Learned-Miller, E.G.[Erik G.],
Sheldon, D.[Daniel],
Gallego, G.[Guillermo],
Bideau, P.[Pia],
The Spatio-Temporal Poisson Point Process:
A Simple Model for the Alignment of Event Camera Data,
ICCV21(13475-13484)
IEEE DOI
2203
Visualization, Tracking, Computational modeling,
Motion segmentation, Brightness, Cameras, Motion and tracking,
Vision for robotics and autonomous vehicles
BibRef
Zhao, J.[Jing],
Xie, J.[Jiyu],
Xiong, R.Q.[Rui-Qin],
Zhang, J.[Jian],
Yu, Z.F.[Zhao-Fei],
Huang, T.J.[Tie-Jun],
Super Resolve Dynamic Scene from Continuous Spike Streams,
ICCV21(2513-2522)
IEEE DOI
2203
Visualization, Image resolution, Dynamics, Superresolution,
Streaming media, Reconstruction algorithms, Cameras,
Low-level and physics-based vision
BibRef
Hu, L.W.[Li-Wen],
Ding, Z.[Ziluo],
Liu, M.Z.[Mian-Zhi],
Ma, L.[Lei],
Huang, T.J.[Tie-Jun],
Learning to Robustly Reconstruct Dynamic Scenes from Low-light Spike
Streams,
ECCV24(XVII: 88-105).
Springer DOI
2412
BibRef
Zhao, J.[Jing],
Xiong, R.Q.[Rui-Qin],
Liu, H.F.[Hang-Fan],
Zhang, J.[Jian],
Huang, T.J.[Tie-Jun],
Spk2ImgNet:
Learning to Reconstruct Dynamic Scene from Continuous Spike Stream,
CVPR21(11991-12000)
IEEE DOI
2111
Correlation, Dynamics, Neural networks,
Streaming media, Reconstruction algorithms, Cameras
BibRef
Hu, Y.H.[Yu-Huang],
Liu, S.C.[Shih-Chii],
Delbruck, T.[Tobi],
v2e: From Video Frames to Realistic DVS Events,
EventVision21(1312-1321)
IEEE DOI
2109
Dynamic Vision Sensor.
Create event-camera data.
Training, Visualization, Lighting, Vision sensors, Tools,
Cameras
BibRef
Peveri, F.[Francesca],
Testa, S.[Simone],
Sabatini, S.P.[Silvio P.],
A Cortically-inspired Architecture for Event-based Visual Motion
Processing: From Design Principles to Real-world Applications,
EventVision21(1395-1402)
IEEE DOI
2109
Visualization, Neuromorphics, Neurons, Neural networks,
Detectors, Spatial filters
BibRef
Nunes, U.M.[Urbano Miguel],
Demiris, Y.F.[Yi-Fannis],
Live Demonstration: Incremental Motion Estimation for Event-based
Cameras by Dispersion Minimisation,
EventVision21(1322-1323)
IEEE DOI
2109
Portable computers, Motion estimation, Cameras,
Minimization, Motion measurement
BibRef
Delbruck, T.[Tobi],
Graca, R.[Rui],
Paluch, M.[Marcin],
Feedback control of event cameras,
EventVision21(1324-1332)
IEEE DOI
2109
Current measurement, Bandwidth,
Production, Vision sensors, Cameras
BibRef
Duwek, H.C.[Hadar Cohen],
Shalumov, A.[Albert],
Tsur, E.E.[Elishai Ezra],
Image Reconstruction from Neuromorphic Event Cameras using
Laplacian-Prediction and Poisson Integration with Spiking and
Artificial Neural Networks,
EventVision21(1333-1341)
IEEE DOI
2109
Visualization, Laplace equations, Neuromorphics, Pipelines, Cameras,
Sensors
BibRef
Jiao, J.H.[Jian-Hao],
Huang, H.Y.[Huai-Yang],
Li, L.[Liang],
He, Z.J.[Zhi-Jian],
Zhu, Y.L.[Yi-Long],
Liu, M.[Ming],
Comparing Representations in Tracking for Event Camera-based SLAM,
EventVision21(1369-1376)
IEEE DOI
2109
Tracking loops, Simultaneous localization and mapping, Tracking, Trajectory
BibRef
Nehvi, J.[Jalees],
Golyanik, V.[Vladislav],
Mueller, F.[Franziska],
Seidel, H.P.[Hans-Peter],
Elgharib, M.[Mohamed],
Theobalt, C.[Christian],
Differentiable Event Stream Simulator for Non-Rigid 3D Tracking,
EventVision21(1302-1311)
IEEE DOI
2109
Training, Surface reconstruction,
Supervised learning, Gesture recognition, Trajectory
BibRef
Muglikar, M.[Manasi],
Gehrig, M.[Mathias],
Gehrig, D.[Daniel],
Scaramuzza, D.[Davide],
How to Calibrate Your Event Camera,
EventVision21(1403-1409)
IEEE DOI
2109
Computational modeling, Robot vision systems, Cameras, Distortion,
Calibration, Sensors
BibRef
Zhang, L.M.[Li-Meng],
Zhang, H.G.[Hong-Guang],
Zhu, C.Y.[Chen-Yang],
Guo, S.S.[Sha-Sha],
Chen, J.[Jihua],
Wang, L.[Lei],
Fine-grained Video Deblurring with Event Camera,
MMMod21(I:352-364).
Springer DOI
2106
BibRef
Kostadinov, D.[Dimche],
Scaramuzza, D.[Davide],
Unsupervised Feature Learning for Event Data:
Direct vs. Inverse Problem Formulation,
ICPR21(5981-5987)
IEEE DOI
2105
Inverse problems, Dynamic range, Cameras,
Encoding, Object recognition
BibRef
Zhao, J.,
Xiong, R.,
Zhao, R.,
Wang, J.,
Ma, S.,
Huang, T.,
Motion Estimation for Spike Camera Data Sequence via Spike Interval
Analysis,
VCIP20(371-374)
IEEE DOI
2102
Cameras, Motion estimation, Trajectory, Image reconstruction,
Data models, Estimation, Dynamics, motion analysis,
motion estimation
BibRef
Zhang, S.[Song],
Zhang, Y.[Yu],
Jiang, Z.[Zhe],
Zou, D.Q.[Dong-Qing],
Ren, J.[Jimmy],
Zhou, B.[Bin],
Learning to See in the Dark with Events,
ECCV20(XVIII:666-682).
Springer DOI
2012
BibRef
Wang, B.S.[Bi-Shan],
He, J.W.[Jing-Wei],
Yu, L.[Lei],
Xia, G.S.[Gui-Song],
Yang, W.[Wen],
Event Enhanced High-quality Image Recovery,
ECCV20(XIII:155-171).
Springer DOI
2011
BibRef
Stoffregen, T.[Timo],
Scheerlinck, C.[Cedric],
Scaramuzza, D.[Davide],
Drummond, T.[Tom],
Barnes, N.M.[Nick M.],
Kleeman, L.[Lindsay],
Mahony, R.[Robert],
Reducing the Sim-to-real Gap for Event Cameras,
ECCV20(XXVII:534-549).
Springer DOI
2011
BibRef
Harrigan, S.,
Coleman, S.,
Kerr, D.,
Yogarajah, P.,
Fang, Z.,
Wu, C.,
Post-Stimulus Time-Dependent Event Descriptor,
ICIP20(385-389)
IEEE DOI
2011
Support vector machines, Vision sensors, Lattices,
Feature extraction, Machine learning
BibRef
Su, B.,
Yu, L.,
Yang, W.,
Event-Based High Frame-Rate Video Reconstruction With A Novel
Cycle-Event Network,
ICIP20(86-90)
IEEE DOI
2011
Image reconstruction, Cameras, Generators, Logic gates, Training,
Generative adversarial networks, Streaming media, Event camera,
GAN
BibRef
Jiang, M.,
Liu, Z.,
Wang, B.,
Yu, L.,
Yang, W.,
Robust Intensity Image Reconstruciton Based On Event Cameras,
ICIP20(968-972)
IEEE DOI
2011
Cameras, Image reconstruction, Streaming media,
Reconstruction algorithms, Mathematical model, Brightness,
Motion blur
BibRef
Liu, D.,
Parra, Á.,
Chin, T.,
Globally Optimal Contrast Maximisation for Event-Based Motion
Estimation,
CVPR20(6348-6357)
IEEE DOI
2008
Upper bound, Estimation, Cameras, Streaming media,
Robot vision systems, Motion estimation, Kernel
BibRef
Gehrig, D.,
Gehrig, M.,
Hidalgo-Carrió, J.,
Scaramuzza, D.,
Video to Events: Recycling Video Datasets for Event Cameras,
CVPR20(3583-3592)
IEEE DOI
PDF File.
2008
Code, Event Camera.
WWW Link. ESIM: Event camera simulator:
WWW Link. Video:
WWW Link. Cameras, Sensors, Semantics, Standards, Brightness, Task analysis,
Machine learning
BibRef
Baldwin, R.W.[R. Wes],
Almatrafi, M.[Mohammed],
Asari, V.[Vijayan],
Hirakawa, K.[Keigo],
Event Probability Mask (EPM) and Event Denoising Convolutional Neural
Network (EDnCNN) for Neuromorphic Cameras,
CVPR20(1698-1707)
IEEE DOI
2008
Cameras, Voltage control, Noise reduction, Neuromorphics, Hardware,
Benchmark testing, Noise measurement
BibRef
Tulyakov, S.[Stepan],
Fleuret, F.[Francois],
Kiefel, M.[Martin],
Gehler, P.[Peter],
Hirsch, M.[Michael],
Learning an Event Sequence Embedding for Dense Event-Based Deep
Stereo,
ICCV19(1527-1537)
IEEE DOI
2004
Event camera.
biomimetics, cameras, image representation,
image sensors, learning (artificial intelligence), Power demand
BibRef
Wang, Q.Y.[Qin-Yi],
Zhang, Y.X.[Ye-Xin],
Yuan, J.S.[Jun-Song],
Lu, Y.L.[Yi-Long],
Space-Time Event Clouds for Gesture Recognition:
From RGB Cameras to Event Cameras,
WACV19(1826-1835)
IEEE DOI
1904
Sense motion, event streams. space-time location of intensity change.
cameras, gesture recognition, image motion analysis, image sensors,
neural net architecture, individual event, space-time location,
Real-time systems
BibRef
Alzugaray, I.,
Chli, M.,
Asynchronous Multi-Hypothesis Tracking of Features with Event Cameras,
3DV19(269-278)
IEEE DOI
1911
BibRef
Earlier:
ACE: An Efficient Asynchronous Corner Tracker for Event Cameras,
3DV18(653-661)
IEEE DOI
1812
Tracking, Cameras, Feature extraction, Visualization,
Streaming media, Robot vision systems, SLAM, dvs, visual odometry,
visual tracking.
image motion analysis, image sequences,
efficient asynchronous corner tracker.
BibRef
Stoffregen, T.[Timo],
Kleeman, L.[Lindsay],
Event Cameras, Contrast Maximization and Reward Functions: An Analysis,
CVPR19(12292-12300).
IEEE DOI
2002
Event cameras asynchronously report timestamped changes in pixel intensity.
BibRef
Scheerlinck, C.[Cedric],
Barnes, N.M.[Nick M.],
Mahony, R.[Robert],
Continuous-Time Intensity Estimation Using Event Cameras,
ACCV18(V:308-324).
Springer DOI
1906
Asynchronous, data-driven measurements of local temporal contrast.
BibRef
Gehrig, D.[Daniel],
Loquercio, A.[Antonio],
Derpanis, K.[Konstantinos],
Scaramuzza, D.[Davide],
End-to-End Learning of Representations for Asynchronous Event-Based
Data,
ICCV19(5632-5642)
IEEE DOI
2004
Event camers: pixel changes.
cameras, convolutional neural nets,
image motion analysis, image representation, image sensors,
Spatiotemporal phenomena
BibRef
Gao, S.,
Guo, G.,
Chen, C.L.P.[C. L. Philip],
Event-Based Incremental Broad Learning System for Object
Classification,
CEFRL19(2989-2998)
IEEE DOI
2004
cameras, convolutional neural nets, image classification,
image sensors, learning (artificial intelligence),
event camera
BibRef
Barua, S.,
Miyatani, Y.,
Veeraraghavan, A.,
Direct face detection and video reconstruction from event cameras,
WACV16(1-9)
IEEE DOI
1606
Cameras
BibRef
Kim, H.[Hanme],
Leutenegger, S.[Stefan],
Davison, A.J.[Andrew J.],
Real-Time 3D Reconstruction and 6-DoF Tracking with an Event Camera,
ECCV16(VI: 349-364).
Springer DOI
1611
Award, ECCV.
BibRef
Kim, H.[Hanme],
Handa, A.[Ankur],
Benosman, R.[Ryad],
Ieng, S.H.[Sio-Hoi],
Davison, A.J.[Andrew J.],
Simultaneous Mosaicing and Tracking with an Event Camera,
BMVC14(xx-yy).
HTML Version.
1410
BibRef
Gobron, S.[Stéphane],
Ahn, J.H.[Jung-Hyun],
Garcia, D.[David],
Silvestre, Q.[Quentin],
Thalmann, D.[Daniel],
Boulic, R.[Ronan],
An Event-Based Architecture to Manage Virtual Human Non-Verbal
Communication in 3D Chatting Environment,
AMDO12(58-68).
Springer DOI
1208
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Differencing Papers -- Ramesh Jain .