Fetching the paper…
Reading the bibliography…
We present the first event-based learning approach for motion segmentation in indoor scenes and the first event-based dataset - EV-IMO - which includes accurate pixel-wise motion masks, egomotion and ground truth depth.
Detecting moving objects
W. B. Thompson and T.-C. Pong · 1990
Earlier work this paper cites.
Passive navigation as a pattern recognition problem
C. Fermüller · 1995
Earlier work this paper cites.
MRF-based motion segmentation exploiting a 2d motion model robust estimation
J.-M. Odobez and P. Bouthemy · 1995
Earlier work this paper cites.
Visual space distortion
C. Fermüller, L. Cheong, and Y. Aloimonos · 1997
Earlier work this paper cites.
A unified approach to moving object detection in 2d and 3d scenes
M. Irani and P. Anandan · 1998
Earlier work this paper cites.
Geometric motion segmentation and model selection
P. H. Torr · 1998
Earlier work this paper cites.
Observability of 3d motion
C. Fermüller and Y. Aloimonos · 2000
Earlier work this paper cites.
Multiple View Geometry in Computer Vision
R. Hartley and A. Zisserman · 2003
Earlier work this paper cites.
Generalized principal component analysis (GPCA)
R. Vidal, Y. Ma, and S. Sastry · 2003
Earlier work this paper cites.
Motion segmentation using occlusions
A. S. Ogale, C. Fermüller, and Y. Aloimonos · 2005
Earlier work this paper cites.
Learning depth from single monocular images
A. Saxena, S. H. Chung, and A. Y. Ng · 2006
Earlier work this paper cites.
Monoslam: Real-time single camera slam
A. J. Davison, I. D. Reid, N. D. Molton, and O. Stasse · 2007
Earlier work this paper cites.
Asynchronous frameless event-based optical flow
R. Benosman, S.-H. Ieng, C. Clercq, C. Bartolozzi, and M. Srinivasan · 2012
Earlier work this paper cites.
Video segmentation by tracing discontinuities in a trajectory embedding
K. Fragkiadaki, G. Zhang, and J. Shi · 2012
Earlier work this paper cites.
Layered segmentation and optical flow estimation over time
D. Sun, E. B. Sudderth, and M. J. Black · 2012
Earlier work this paper cites.
Low-latency localization by active led markers tracking using a dynamic vision sensor
A. Censi, J. Strubel, C. Brandli, T. Delbruck, and D. Scaramuzza · 2013
Cited alongside, same era.
Simultaneous localization and mapping for event-based vision systems
D. Weikersdorfer, R. Hoffmann, and J. Conradt · 2013
Cited alongside, same era.
Contour motion estimation for asynchronous event-driven cameras
F. Barranco, C. Fermüller, and Y. Aloimonos · 2014
Cited alongside, same era.
Event-based visual flow
R. Benosman, C. Clercq, X. Lagorce, S.-H. Ieng, and C. Bartolozzi · 2014
Cited alongside, same era.
Depth map prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
Cited alongside, same era.
Simultaneous mosaicing and tracking with an event camera
H. Kim, A. Handa, R. Benosman, S.-H. Ieng, and A. J. Davison · 2014
Feature detection and tracking with the dynamic and active-pixel vision sensor (DAVIS)
D. Tedaldi, G. Gallego, E. Mueggler, and D. Scaramuzza · 2016
Later among the works it cites.
Deep3d: Fully automatic 2d-to-3d video conversion with deep convolutional neural networks
J. Xie, R. Girshick, and A. Farhadi · 2016
Later among the works it cites.
Block-matching optical flow for dynamic vision sensors: Algorithm and FPGA implementation
M. Liu and T. Delbruck · 2017
Later among the works it cites.
Real-time panoramic tracking for event cameras
C. Reinbacher, G. Munda, and T. Pock · 2017
Later among the works it cites.
Sfm-net: Learning of structure and motion from video, 2017
S. Vijayanarasimhan, S. Ricco, C. Schmid, R. Sukthankar, and K. Fragkiadaki · 2017
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.
Bio-inspired motion estimation with event-driven sensors
F. Barranco, C. Fermüller, and Y. Aloimonos · 2015
Cited alongside, same era.
On event-based optical flow detection
T. Brosch, S. Tschechne, and H. Neumann · 2015
Cited alongside, same era.
Learning to segment moving objects in videos
K. Fragkiadaki, P. Arbelaez, P. Felsen, and J. Malik · 2015
Cited alongside, same era.
Lifetime estimation of events from dynamic vision sensors
E. Mueggler, C. Forster, N. Baumli, G. Gallego, and D. Scaramuzza · 2015
Cited alongside, same era.
U-net: Convolutional Networks for Biomedical Image Segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
Event-based, 6-dof camera tracking for high-speed applications
G. Gallego, J. E. A. Lund, E. Mueggler, H. Rebecq, T. Delbrück, and D. Scaramuzza · 2016
Cited alongside, same era.
C. Wang, J. M. Buenaposada, R. Zhu, and S. Lucey · 2017
Later among the works it cites.
Unsupervised learning of depth and ego-motion from video
T. Zhou, M. Brown, N. Snavely, and D. G. Lowe · 2017
Later among the works it cites.
Event-based visual inertial odometry
A. Z. Zhu, N. Atanasov, and K. Daniilidis · 2017
Later among the works it cites.
The best of both worlds: combining cnns and geometric constraints for hierarchical motion segmentation
P. Bideau, A. RoyChowdhury, R. R. Menon, and E. Learned-Miller · 2018
Later among the works it cites.
Unsupervised learning of depth and ego-motion from monocular video using 3d geometric constraints
R. Mahjourian, M. Wicke, and A. Angelova · 2018
Later among the works it cites.
Event-based moving object detection and tracking
A. Mitrokhin, C. Fermüller, C. Parameshwara, and Y. Aloimonos · 2018
Later among the works it cites.
LEGO: learning edge with geometry all at once by watching videos
Z. Yang, P. Wang, Y. Wang, W. Xu, and R. Nevatia · 2018
Later among the works it cites.
Unsupervised learning of dense optical flow, depth and egomotion from sparse event data
C. Ye, A. Mitrokhin, C. Fermüller, J. A. Yorke, and Y. Aloimonos · 2018
Later among the works it cites.
Geonet: Unsupervised learning of dense depth, optical flow and camera pose
Z. Yin and J. Shi · 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.