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I am a Ph.D. student at Johns Hopkins University in the department of Computer Science under the guidance of Prof. Rama Chellappa. I am currently working on Computer Vision and Machine Learning, specifically on a few-shot learning, multimodal learning, generative AI, including diffusion models and large language models. Prior to that, I obtained M.S.(by Research) degree from Dept. of Computer Science, Indian Institute of Technology Kharagpur. I am honored to be awarded as an Amazon Fellow. Email / CV / Google Scholar / Twitter / Github |
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My broad research interest lies in the intersection of Machine Learning and Computer Vision. Specifically, I have worked on few-shot learning, multi-modal learning, generative models, foundational models, and Large Language models. |
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Aniket Roy, Shubhankar Borse, Shreya Kadambi, Risheek Garrepalli, Debasmit Das, Shweta Mahajan, Hyojin Park, Ankita Nayak, Rama Chellappa, Munawar Hayat, Fatih Porikli Submitted We perform content-style personalization using cycle-consistency and diffusion layer priors. |
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Aniket Roy, Maitreya Suin, Anshul Shah, Ketul Shah, Jiang Liu, Rama Chellappa Submitted We propose a kurtosis loss to generate better quality images |
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Aniket Roy, Anshul Shah*, Ketul Shah*, Anirban Roy, Rama Chellappa WACV 2025 We use pretrained caption and diffusion model to generate semantic augmentations. |
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Aniket Roy, Anirban Roy, Soma Mitra, Kuntal Ghosh ICIP 2024 We curate a dataset and benchmark visual illusions. We also investigate illusion understanding capabilities of diffusion models. |
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Basudha Pal, Aniket Roy, RP Kathirvel, AJ O’Toole, R Chellappa IJCB 2024 We mitigate gender and racial bias using diffusion model generated images. |
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Anshul Shah, Aniket Roy*, Ketul Shah*, Shlok Mishra, David Jacobs, Anoop Cherian, Rama Chellappa CVPR 2023 We hallucinate latent postives for learning skeleton encoders without labels |
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Mahyar Fazlyab*, Taha Entesari*, Aniket Roy, Rama Chellappa NeurIPS 2023 We propose a differentiable regularizer that is a lower bound on the distance of the data points to the classification boundary. |
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Aniket Roy, Anshul Shah, Ketul Shah, Prithviraj Dhar, Anoop Cherian, Rama Chellappa NeurIPS 2022 We propose hard mixup to improve few shot learning |
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Aniket Roy, Anshul Shah*, Ketul Shah*, Anirban Roy, Rama Chellappa Under Submission We leverage the recent success of the generative models for few-shot learning arXiv |
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Aniket Roy*, Shraman Pramanick*, Vishal Patel WACV 2022 We propose optimal transport for multimodal fusion |
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Prithviraj Dhar*, Josh Gleason*, Aniket Roy, Carlos Castillo, Rama Chellappa ICCV 2021 We propose an adversarial framework for gender and racial bias mitigation |
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Prithviraj Dhar, Josh Gleason, Aniket Roy, Carlos Castillo, P.J. Philips, Rama Chellappa arxiv We propose a knowledge distillation based framework for gender and racial bias mitigation |
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Aniket Roy, Rahul Dixit, Ruchira Naskar and Rajat Subhra Chakraborty Springer, ISBN: 978-9811076435 The book covers topics in digital image forensics |
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Aniket Roy, Rajat Subhra Chakraborty IEEE Transactions on Circuits and Systems for Video Technology (IEEE TCSVT) We performed theoretical analysis of Prediction Error Expansion based Reversible Image Watermarking |
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Diangrati Tariang, Prithviraj Sengupta, Aniket Roy, Rajat Subhra Chakraborty and Ruchira Naskar IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2019 We propose a deep convolutional recurrent attention model for classifying computer generated and natural images. |
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Aniket Roy, Diangrati Tariang, Rajat Subhra Chakraborty and Ruchira Naskar IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2018 We propose to use Discrete Cosine Transform Residual Feature Based Filtering Forgery and Splicing Detection |
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Aniket Roy, Rajat Subhra Chakraborty, Udaya Sameer, Ruchira Naskar IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2017 We propose to use Discrete Cosine Transform Residual Feature for Camera Source Identification |
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Aniket Roy, Akhil Konda and Rajat Subhra Chakraborty IEEE International Conference on Image Processing (ICIP) 2017 We use Rotated Local Binary Pattern features for similar but genuine object based forgery |
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Diangarti Tariang, Aniket Roy, Rajat Subhra Chakraborty and Ruchira Naskar IEEE International Conference on Multimedia and Expo (ICMEW) Workshops 2017 We detect and localize JPEG image forgery based on noise correlation |
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Aniket Roy and Rajat Subhra Chakraborty International Workshop on Digital-Forensics and Watermarking (IWDW), 2016 We performed theoretical analysis of Prediction Error Expansion Based Reversible Watermarking |
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Aniket Roy, Arpan Kumar Maiti and Kuntal Ghosh International Journal of Image and Graphics (IJIG) We proposed a human visual system inspired watermarking scheme and performed robustness analysis |
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Aniket Roy, Rajat Subhra Chakraborty and Ruchira Naskar ICISS 2015 We propose a reversible color image watermarking scheme and perform information theoretic analysis |
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