Sadeep Jayasumana

Google (United States) — United States

Computer Science · Physical Sciences

12h-index3.5kcitations34works32.82yr avg
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Research Topics

Face and Expression Recognition(10), Advanced Image and Video Retrieval Techniques(8), Domain Adaptation and Few-Shot Learning(8), Video Surveillance and Tracking Methods(6), Image Retrieval and Classification Techniques(6)

Publications34 total

LatentCRF: Continuous CRF for Efficient Latent Diffusion
arXiv (Cornell University)·2024Open Access
Efficient Document Ranking with Learnable Late Interactions
arXiv (Cornell University)·2024· 3 citedOpen Access
MarkovGen: Structured Prediction for Efficient Text-to-Image Generation
2024· 1 cited
Rethinking FID: Towards a Better Evaluation Metric for Image Generation
2024· 127 cited
Rethinking FID: Towards a Better Evaluation Metric for Image Generation
arXiv (Cornell University)·2023· 8 citedOpen Access
MarkovGen: Structured Prediction for Efficient Text-to-Image Generation
arXiv (Cornell University)·2023Open Access
EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval
arXiv (Cornell University)·2023· 4 citedOpen Access
When does mixup promote local linearity in learned representations?
arXiv (Cornell University)·2022Open Access
Disentangling Sampling and Labeling Bias for Learning in Large-Output\n Spaces
arXiv (Cornell University)·2021· 1 citedOpen Access
Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces
arXiv (Cornell University)·2021· 3 citedOpen Access
Less is more: Selecting informative and diverse subsets with balancing constraints
arXiv (Cornell University)·2021· 2 citedOpen Access
Balancing Constraints and Submodularity in Data Subset Selection.
arXiv (Cornell University)·2021· 2 citedOpen Access
Kernelized Classification in Deep Networks
arXiv (Cornell University)·2020Open Access
Long-tail learning via logit adjustment
arXiv (Cornell University)·2020· 52 citedOpen Access
Bipartite Conditional Random Fields for Panoptic Segmentation
2020· 1 cited
Bipartite Conditional Random Fields for Panoptic Segmentation
arXiv (Cornell University)·2019· 3 citedOpen Access
Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction
IEEE Signal Processing Magazine·2018· 137 cited
Higher Order Conditional Random Fields in Deep Neural Networks
Lecture notes in computer science·2016· 12 citedOpen Access
Conditional Random Fields as Recurrent Neural Networks
2015· 2.4k citedOpen Access
Higher Order Potentials in End-to-End Trainable Conditional Random Fields
arXiv (Cornell University)·2015· 15 citedOpen Access
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Frequent Co-authors

Mathieu Salzmann(12), Hongdong Li(11), Mehrtash Harandi(11), Richard Hartley(10), Andreas Veit(8), Daniel Gläsner(7), Sanjiv Kumar(7), Sanjiv Kumar(7), Aditya Krishna Menon(6), Srikumar Ramalingam(5), Ayan Chakrabarti(5), Ankit Singh Rawat(5), Shuai Zheng(4), Philip H. S. Torr(4), Srikumar Ramalingam(4), Bernardino Romera‐Paredes(3), Anurag Arnab(3), Wittawat Jitkrittum(3), Sashank J. Reddi(3), Kanchana Ranasinghe(3)