Research
I am interested in computer vision, deep learning, generative models, image processing, graphics, and applied machine learning. Most of my recent research focuses on text style manipulation and human pose transformation. Some publications are highlighted.
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TIPS: Text-Induced Pose Synthesis
Prasun Roy,
Subhankar Ghosh,
Saumik Bhattacharya,
Umapada Pal,
Michael Blumenstein
ECCV, 2022
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arXiv /
BibTex
We address the structural bias in pose-guided person image generation techniques with a text-conditioned human pose transformation strategy.
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STEFANN: Scene Text Editor using Font Adaptive Neural Network
Prasun Roy,
Saumik Bhattacharya,
Subhankar Ghosh,
Umapada Pal
CVPR, 2020
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arXiv /
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We introduce a technique for character-level realistic text modification in a scene by disentangling the task into dedicated shape and color transformation objectives.
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Exploring Mutual Cross-Modal Attention for Context-Aware Human Affordance Generation
Prasun Roy,
Saumik Bhattacharya,
Subhankar Ghosh,
Umapada Pal,
Michael Blumenstein
arXiv, 2025
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arXiv /
BibTex
By mutually cross-attending two different spatial feature spaces, we encode the global scene context for semantically meaningful affordance generation.
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FASTER: A Font-Agnostic Scene Text Editing and Rendering Framework
Alloy Das,
Sanket Biswas,
Prasun Roy,
Subhankar Ghosh,
Umapada Pal,
Michael Blumenstein,
Josep Lladós,
Saumik Bhattacharya
WACV, 2025 (Oral presentation)
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arXiv /
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By adopting a cascaded attention mechanism, we perform word-level style and content translation for realistic text manipulation in a scene.
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Semantically Consistent Person Image Generation
Prasun Roy,
Saumik Bhattacharya,
Subhankar Ghosh,
Umapada Pal,
Michael Blumenstein
ICPR, 2024
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arXiv /
BibTex
Using a parsing map-based representation, we propose a method for introducing a new person into a scene such that the inserted person is semantically consistent with the existing individuals.
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d-Sketch: Improving Visual Fidelity of Sketch-to-Image Translation with Pretrained Latent Diffusion Models without Retraining
Prasun Roy,
Saumik Bhattacharya,
Subhankar Ghosh,
Umapada Pal,
Michael Blumenstein
ICPR, 2024
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arXiv /
BibTex
A small trainable latent mapping network lets you perform photorealistic sketch-to-image translation using a pretrained text-to-image diffusion model without retraining.
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Multi-scale Attention Guided Pose Transfer
Prasun Roy,
Saumik Bhattacharya,
Subhankar Ghosh,
Umapada Pal
Pattern Recognition, 2023
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arXiv /
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Cascaded attention at every feature resolution improves the generated image quality by retaining both low-frequency and high-frequency visual attributes in a structurally guided end-to-end human pose transformation.
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Scene Aware Person Image Generation through Global Contextual Conditioning
Prasun Roy,
Subhankar Ghosh,
Saumik Bhattacharya,
Umapada Pal,
Michael Blumenstein
ICPR, 2022
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arXiv /
BibTex
Using a keypoint-based representation, we propose a method for introducing a new person into a scene such that the inserted person is semantically consistent with the existing individuals.
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Effects of Degradations on Deep Neural Network Architectures
Prasun Roy,
Subhankar Ghosh,
Saumik Bhattacharya,
Umapada Pal
arXiv, 2018
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arXiv /
BibTex
A study on how different image degradation models impact the performance decay of deep neural networks unveils fascinating insights for substantially improving noise tolerance at the expense of slight performance trade-offs.
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Yes. I'm also using Jon Barron's website template.😅
Copyright © 2025 Prasun Roy.✨
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