Fetching the paper…
Reading the bibliography…
We introduce the first very large detection dataset for event cameras.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, P. Haffner, et al · 1998
Earlier work this paper cites.
A comparison of affine region detectors
K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool · 2005
Earlier work this paper cites.
One-shot learning of object categories
L. Fei-Fei, R. Fergus, and P. Perona · 2006
Earlier work this paper cites.
Caltech-256 object category dataset
G. Griffin, A. Holub, and P. Perona · 2007
Earlier work this paper cites.
A 128x128 120db 15us latency asynchronous temporal contrast vision sensor
P. Lichtsteiner, C. Posch, and T. Delbruck · 2008
Earlier work this paper cites.
Imagenet: A Large-Scale Hierarchical Image Database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
Earlier work this paper cites.
A QVGA 143 dB Dynamic Range Frame-Free PWM Image Sensor With Lossless Pixel-Level Video Compression and Time-Domain CDS
C. Posch, D. Matolin, and R. Wohlgenannt · 2011
Earlier work this paper cites.
Pedestrian detection: An evaluation of the state of the art
P. Dollar, C. Wojek, B. Schiele, and P. Perona · 2012
Earlier work this paper cites.
ImageNet Classification with Deep Convolutional Neural Networks
A. Krizhevsky, I. Sutskever, and G. Hinton · 2012
Earlier work this paper cites.
Recognizing 50 human action categories of web videos
K. K. Reddy and M. Shah · 2013
Earlier work this paper cites.
A 128 x 128 1.5% contrast sensitivity 0.9% fpn 3
T. Serrano-Gotarredona and B. Linares-Barranco · 2013
Earlier work this paper cites.
Microsoft COCO: Common Objects in Context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. Zitnick · 2014
Earlier work this paper cites.
The visual object tracking vot2015 challenge results
M. Kristan, J. Matas, A. Leonardis, M. Felsberg, L. Cehovin, G. Fernandez, T. Vojir, G. Hager, G. Nebehay, and R. Pflugfelder · 2015
Earlier work this paper cites.
Spatiotemporal features for asynchronous event-based data
X. Lagorce, S.-H. Ieng, X. Clady, M. Pfeiffer, and R. B. Benosman · 2015
Earlier work this paper cites.
Deep learning
Y. LeCun, Y. Bengio, and G. Hinton · 2015
Cited alongside, same era.
Converting static image datasets to spiking neuromorphic datasets using saccades
G. Orchard, A. Jayawant, G. K. Cohen, and N. Thakor · 2015
Cited alongside, same era.
Poker-dvs and mnist-dvs. their history, how they were made, and other details
T. Serrano-Gotarredona and B. Linares-Barranco · 2015
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Dvs benchmark datasets for object tracking, action recognition, and object recognition
Y. Hu, H. Liu, M. Pfeiffer, and T. Delbruck · 2016
Cited alongside, same era.
A low power, fully event-based gesture recognition system
A. Amir, B. Taba, D. Berg, T. Melano, J. McKinstry, C. Di Nolfo, T. Nayak, A. Andreopoulos, G. Garreau, M. Mendoza, et al · 2017
Esim: an open event camera simulator
H. Rebecq, D. Gehrig, and D. Scaramuzza · 2018
Later among the works it cites.
Hats: Histograms of averaged time surfaces for robust event-based object classification
A. Sironi, M. Brambilla, N. Bourdis, X. Lagorce, and R. Benosman · 2018
Later among the works it cites.
The multivehicle stereo event camera dataset: An event camera dataset for 3d perception
A. Z. Zhu, D. Thakur, T. Özaslan, B. Pfrommer, V. Kumar, and K. Daniilidis · 2018
Later among the works it cites.
Ev-flownet: Self-supervised optical flow estimation for event-based cameras
A. Z. Zhu, L. Yuan, K. Chaney, and K. Daniilidis · 2018
Later among the works it cites.
Graph-based object classification for neuromorphic vision sensing
Y. Bi, A. Chadha, A. Abbas, , E. Bourtsoulatze, and Y. Andreopoulos · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Ddd17: End-to-end davis driving dataset
J. Binas, D. Neil, S.-C. Liu, and T. Delbruck · 2017
Cited alongside, same era.
Live demonstration: A 768
M. Guo, J. Huang, and S. Chen · 2017
Cited alongside, same era.
4.1 a 640×480 dynamic vision sensor with a 9µm pixel and 300meps address-event representation
B. Son, Y. Suh, S. Kim, H. Jung, J.-S. Kim, C.-W. Shin, K. Park, K. Lee, J. M. Park, J. Woo, Y. Roh, H. Lee, Y. M. Wang, I. A. Ovsiannikov, and H. Ryu · 2017
Cited alongside, same era.
Real-time clustering and multi-target tracking using event-based sensors
F. Barranco, C. Fermuller, and E. Ros · 2018
Cited alongside, same era.
Pseudo-labels for supervised learning on dynamic vision sensor data, applied to object detection under ego-motion
N. F. Y. Chen · 2018
Cited alongside, same era.
O (n)-space spatiotemporal filter for reducing noise in neuromorphic vision sensors
A. Khodamoradi and R. Kastner · 2018
Cited alongside, same era.
E. Calabrese, G. Taverni, C. Awai Easthope, S. Skriabine, F. Corradi, L. Longinotti, K. Eng, and T. Delbruck · 2019
Later among the works it cites.
G. Gallego, T. Delbruck, G. Orchard, C. Bartolozzi, B. Taba, A. Censi, S. Leutenegger, A. Davison, J. Conradt, K. Daniilidis, et al · 2019
Later among the works it cites.
Video to events: Bringing modern computer vision closer to event cameras
d. Gehrig, M. Gehrig, J. Hidalgo-Carrio, and D. Scaramuzza · 2019
Later among the works it cites.
Edge detection for event cameras using intra-pixel-area events
S. Lee, H. Kim, and H. J. Kim · 2019
Later among the works it cites.
Speed invariant time surface for learning to detect corner points with event-based cameras
J. Manderscheid, A. Sironi, N. Bourdis, D. Migliore, and V. Lepetit · 2019
Later among the works it cites.
Neuromorphic benchmark datasets for pedestrian detection, action recognition, and fall detection
S. Miao, G. Chen, X. Ning, Y. Zi, K. Ren, Z. Bing, and A. C. Knoll · 2019
Later among the works it cites.
Ev-imo: Motion segmentation dataset and learning pipeline for event cameras
A. Mitrokhin, C. Ye, C. Fermuller, Y. Aloimonos, and T. Delbruck · 2019
Later among the works it cites.
Events-to-video: Bringing modern computer vision to event cameras
H. Rebecq, R. Ranftl, V. Koltun, and D. Scaramuzza · 2019
Later among the works it cites.
Ced: Color event camera dataset
C. Scheerlinck, H. Rebecq, T. Stoffregen, N. Barnes, R. Mahony, and D. Scaramuzza · 2019
Later among the works it cites.