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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
31832015
Long-Tail Learning via Logit Adjustment
AK Menon, S Jayasumana, AS Rawat, H Jain, A Veit, S Kumar
ICLR, 2021
6342021
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
3542013
Higher order conditional random fields in deep neural networks
A Arnab, S Jayasumana, S Zheng, PHS Torr
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
2842016
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
2652015
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
1652018
Expanding the family of grassmannian kernels: An embedding perspective
MT Harandi, M Salzmann, S Jayasumana, R Hartley, H Li
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
1122014
Dalong Du, Chang Huang, and Philip HS Torr. 2015. Conditional random fields as recurrent neural networks
S Zheng, S Jayasumana, B Romera-Paredes, V Vineet, Z Su
Proceedings of the IEEE international conference on computer vision, 1529-1537, 2015
1112015
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
482015
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
432014
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
422013
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
342015
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
292013
In defense of dual-encoders for neural ranking
A Menon, S Jayasumana, AS Rawat, S Kim, S Reddi, S Kumar
International Conference on Machine Learning, 15376-15400, 2022
192022
Rethinking FID: Towards a Better Evaluation Metric for Image Generation
S Jayasumana, S Ramalingam, A Veit, D Glasner, A Chakrabarti, ...
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024
172024
Disentangling sampling and labeling bias for learning in large-output spaces
AS Rawat, AK Menon, W Jitkrittum, S Jayasumana, F Yu, S Reddi, ...
International conference on machine learning, 8890-8901, 2021
102021
Bipartite Conditional Random Fields for Panoptic Segmentation
S Jayasumana, K Ranasinghe, M Jayawardhana, S Liyanaarachchi, ...
British Machine Vision Conference (BMVC), 2020
102020
Kernelized classification in deep networks
S Jayasumana, S Ramalingam, S Kumar
arXiv preprint arXiv:2012.09607, 2020
92020
Kernels on Riemannian manifolds
S Jayasumana, R Hartley, M Salzmann
Riemannian computing in computer vision, 45-67, 2016
92016
Embeddistill: A geometric knowledge distillation for information retrieval
S Kim, AS Rawat, M Zaheer, S Jayasumana, V Sadhanala, W Jitkrittum, ...
arXiv preprint arXiv:2301.12005, 2023
52023
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