Sadeep Jayasumana

According to our database, Sadeep Jayasumana authored at least 23 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Rethinking FID: Towards a Better Evaluation Metric for Image Generation.

Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar

CoRR, 2024

2023

SPEGTI: Structured Prediction for Efficient Generative Text-to-Image Models.

Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar

CoRR, 2023

EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval.

Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar

CoRR, 2023

2022

When does mixup promote local linearity in learned representations?

Arslan Chaudhry, Aditya Krishna Menon, Andreas Veit, Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar

CoRR, 2022

In defense of dual-encoders for neural ranking.

Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar

Proceedings of the International Conference on Machine Learning, 2022

2021

Balancing Constraints and Submodularity in Data Subset Selection.

Srikumar Ramalingam, Daniel Glasner, Kaushal Patel, Raviteja Vemulapalli, Sadeep Jayasumana, Sanjiv Kumar

CoRR, 2021

Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces.

Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

Proceedings of the 38th International Conference on Machine Learning, 2021

Long-tail learning via logit adjustment.

Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Kernelized Classification in Deep Networks.

Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar

CoRR, 2020

Bipartite Conditional Random Fields for Panoptic Segmentation.

Sadeep Jayasumana, Kanchana Ranasinghe, Sahan Liyanaarachchi, Mayuka Jayawardhana, Harsha Ranasinghe, Sina Samangooei

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

Bipartite Conditional Random Fields for Panoptic Segmentation.

Sadeep Jayasumana, Kanchana Ranasinghe, Mayuka Jayawardhana, Sahan Liyanaarachchi, Harsha Ranasinghe

CoRR, 2019

2018

Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction.

Anurag Arnab, Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Måns Larsson, Alexander Kirillov, Bogdan Savchynskyy, Carsten Rother, Fredrik Kahl, Philip H. S. Torr

IEEE Signal Process. Mag., 2018

2016

Higher Order Conditional Random Fields in Deep Neural Networks.

Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H. S. Torr

Proceedings of the Computer Vision - ECCV 2016, 2016

2015

Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels.

Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Higher Order Potentials in End-to-End Trainable Conditional Random Fields.

Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H. S. Torr

CoRR, 2015

Conditional Random Fields as Recurrent Neural Networks.

Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Prototypical Priors: From Improving Classification to Zero-Shot Learning.

Saumya Jetley, Bernardino Romera-Paredes, Sadeep Jayasumana, Philip H. S. Torr

Proceedings of the British Machine Vision Conference 2015, 2015

2014

Expanding the Family of Grassmannian Kernels: An Embedding Perspective.

Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Sadeep Jayasumana, Richard I. Hartley, Hongdong Li

Proceedings of the Computer Vision - ECCV 2014, 2014

Optimizing over Radial Kernels on Compact Manifolds.

Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013

Improved Server Architecture for Highly Efficient Message Mediation.

Hiranya Jayathilaka, Pradeep R. Fernando, Paul Fremantle, Kasun Indrasiri, Dushan Abeyruwan, Supun Kamburugamuve, Sadeep Jayasumana, Sanjiva Weerawarana, Srinath Perera

Proceedings of the 15th International Conference on Information Integration and Web-based Applications & Services, 2013

A Framework for Shape Analysis via Hilbert Space Embedding.

Sadeep Jayasumana, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi

Proceedings of the IEEE International Conference on Computer Vision, 2013

Combining Multiple Manifold-Valued Descriptors for Improved Object Recognition.

Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi

Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 2013

Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices.

Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013