19.3.1.1 Event Camera

Chapter Contents (Back)
Event Camera. Motion, Differencing. Reports events of significant pixel intensity changes. Capture the motion, not the contents of the image. Helps for privacy in analysis.
See also Event Camera Opeical Flow.

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
computer vision 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
Computer vision 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, Computer architecture, 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, Computer architecture, 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.[Qiugang], Liu, G.[Guisong], Xie, X.[Xiurui], Tao, R.[Ran], Zhang, M.[Malu], Tang, H.[Huajin],
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


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.[Yuanlin], 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], 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 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.[Lexuan], Hua, G.[Guang], Zhang, H.[Haijian], 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

Messikommer, N.[Nico], Fang, C.[Carter], Gehrig, M.[Mathias], Scaramuzza, D.[Davide],
Data-Driven Feature Tracking for Event Cameras,
CVPR23(5642-5651)
IEEE DOI 2309

WWW Link. 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

Lin, S.N.[Song-Nan], Ma, Y.[Ye], Guo, Z.H.[Zhen-Hua], Wen, B.[Bihan],
DVS-Voltmeter: Stochastic Process-Based Event Simulator for Dynamic Vision Sensors,
ECCV22(VII:578-593).
Springer DOI 2211
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

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 .


Last update:Nov 26, 2024 at 16:40:19