Sadeep Jayasumana
Sadeep Jayasumana
Research Scientist, Google Research
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Conditional Random Fields as Recurrent Neural Networks
S Zheng, S Jayasumana, B Romera-Paredes, V Vineet, Z Su, D Du, ...
IEEE International Conference on Computer Vision (ICCV), 2015
26322015
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices
S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, 73-80, 2013
3072013
Higher order conditional random fields in deep neural networks
A Arnab, S Jayasumana, S Zheng, PHS Torr
European Conference on Computer Vision, 524-540, 2016
2312016
Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels
S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015
1742015
Conditional random fields meet deep neural networks for semantic segmentation: Combining probabilistic graphical models with deep learning for structured prediction
A Arnab, S Zheng, S Jayasumana, B Romera-Paredes, M Larsson, ...
IEEE Signal Processing Magazine 35 (1), 37-52, 2018
1042018
Expanding the family of grassmannian kernels: An embedding perspective
MT Harandi, M Salzmann, S Jayasumana, R Hartley, H Li
European Conference on Computer Vision, 408-423, 2014
882014
Long-Tail Learning via Logit Adjustment
AK Menon, S Jayasumana, AS Rawat, H Jain, A Veit, S Kumar
ICLR, 2021
582021
A framework for shape analysis via hilbert space embedding
S Jayasumana, M Salzmann, H Li, M Harandi
Proceedings of the IEEE International Conference on Computer Vision, 1249-1256, 2013
372013
Optimizing Over Radial Kernels on Compact Manifolds
S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 2014
292014
Higher order potentials in end-to-end trainable conditional random fields
A Arnab, S Jayasumana, S Zheng, PHS Torr
arXiv preprint arXiv:1511.08119 2, 2015
262015
Prototypical Priors: From Improving Classification to Zero-Shot Learning
S Jetley, B Romera-Paredes, S Jayasumana, P Torr
The British Machine Vision Conference (BMVC), 2015
262015
Combining multiple manifold-valued descriptors for improved object recognition
S Jayasumana, R Hartley, M Salzmann, H Li, M Harandi
2013 International Conference on Digital Image Computing: Techniques and …, 2013
242013
Kernels on Riemannian manifolds
S Jayasumana, R Hartley, M Salzmann
Riemannian Computing in Computer Vision, 45-67, 2016
52016
Bipartite Conditional Random Fields for Panoptic Segmentation
S Jayasumana, K Ranasinghe, M Jayawardhana, S Liyanaarachchi, ...
British Machine Vision Conference (BMVC), 2020
32020
Improved server architecture for highly efficient message mediation
H Jayathilaka, P Fernando, P Fremantle, K Indrasiri, D Abeyruwan, ...
Proceedings of International Conference on Information Integration and Web …, 2013
22013
Kernelized Classification in Deep Networks
S Jayasumana, S Ramalingam, S Kumar
arXiv preprint arXiv:2012.09607, 2020
12020
Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces
AS Rawat, AK Menon, W Jitkrittum, S Jayasumana, FX Yu, S Reddi, ...
arXiv preprint arXiv:2105.05736, 2021
2021
Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces
A Singh Rawat, A Krishna Menon, W Jitkrittum, S Jayasumana, FX Yu, ...
arXiv e-prints, arXiv: 2105.05736, 2021
2021
Balancing Constraints and Submodularity in Data Subset Selection
S Ramalingam, D Glasner, K Patel, R Vemulapalli, S Jayasumana, ...
arXiv preprint arXiv:2104.12835, 2021
2021
Disentangling sampling and labeling bias for learning in large-output spaces
AK Menon, AS Rawat, F Yu, S Jayasumana, S Kumar, S Reddi, ...
2021
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Articles 1–20