Search Results for author: Shyamgopal Karthik

Found 9 papers, 5 papers with code

BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks

1 code implementation14 Jul 2022 Uddeshya Upadhyay, Shyamgopal Karthik, Yanbei Chen, Massimiliano Mancini, Zeynep Akata

Moreover, many of the high-performing deep learning models that are already trained and deployed are non-Bayesian in nature and do not provide uncertainty estimates.

Autonomous Driving Deblurring +2

KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning

1 code implementation CVPR 2022 Shyamgopal Karthik, Massimiliano Mancini, Zeynep Akata

The goal of open-world compositional zero-shot learning (OW-CZSL) is to recognize compositions of state and objects in images, given only a subset of them during training and no prior on the unseen compositions.

Compositional Zero-Shot Learning

Learning From Long-Tailed Data With Noisy Labels

no code implementations25 Aug 2021 Shyamgopal Karthik, Jérome Revaud, Boris Chidlovskii

In addition, the resulting learned representations are also remarkably robust to label noise, when fine-tuned with an imbalance- and noise-resistant loss function.

Self-Supervised Learning

No Cost Likelihood Manipulation at Test Time for Making Better Mistakes in Deep Networks

1 code implementation1 Apr 2021 Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania, Vineet Gandhi

There has been increasing interest in building deep hierarchy-aware classifiers that aim to quantify and reduce the severity of mistakes, and not just reduce the number of errors.

Amending Mistakes Post-hoc in Deep Networks by Leveraging Class Hierarchies

no code implementations ICLR 2021 Shyamgopal Karthik, Ameya Prabhu, Puneet K. Dokania, Vineet Gandhi

There has been increasing interest in building deep hierarchy-aware classifiers, aiming to quantify and reduce the severity of mistakes and not just count the number of errors.

Simple Unsupervised Multi-Object Tracking

no code implementations4 Jun 2020 Shyamgopal Karthik, Ameya Prabhu, Vineet Gandhi

Multi-object tracking has seen a lot of progress recently, albeit with substantial annotation costs for developing better and larger labeled datasets.

Multi-Object Tracking

Exploring 3 R's of Long-term Tracking: Re-detection, Recovery and Reliability

no code implementations27 Oct 2019 Shyamgopal Karthik, Abhinav Moudgil, Vineet Gandhi

Recent works have proposed several long term tracking benchmarks and highlight the importance of moving towards long-duration tracking to bridge the gap with application requirements.

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