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Sriram Chellappan

2 accepted papers

2026

Generative Adversarial Perturbations with Cross-paradigm Transferability on Localized Crowd Counting

CVPR 2026

State-of-the-art crowd counting and localization are primarily modeled using two paradigms: density maps and point regression. Given the field's security ramifications, there is active interest in model robustness against adversarial attacks. Recent studies have demonstrated transferability across d

Cited by 0SourcecodeScholar
2021

A Large-Scale Study of Machine Translation in Turkic Languages

EMNLP 2021main

Recent advances in neural machine translation (NMT) have pushed the quality of machine translation systems to the point where they are becoming widely adopted to build competitive systems. However, there is still a large number of languages that are yet to reap the benefits of NMT. In this paper, we…

Sriram Chellappan — accepted AI-conference papers · AIConfPaper