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Hyper-ICL: Attention Calibration with Hyperbolic Anchor Distillation for Multimodal In-Context Learning.
NA Talemi, H Kashiani, F Afghah
International Conference on Machine Learning (ICML), 2026.
arxiv /
Poster/
Slides
We propose Hyper-ICL, a lightweight framework for demonstration-free multimodal in-context learning that reconstructs demonstration effects through logit-level attention calibration, query-adaptive modulation, and layer-wise hyperbolic anchor distillation.
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WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring.
M Habibpour, NA Talemi, J Spodnik, CJ Khoury, F Afghah
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W), 2026.
arxiv /
code
We introduce WildFireVQA, the first visual question answering benchmark designed specifically for aerial wildfire monitoring. Built on aligned RGB images, color-mapped thermal visualizations, and radiometric thermal TIFFs, WildFireVQA enables temperature-grounded multimodal reasoning for safety-critical wildfire intelligence, including fire detection, hotspot localization, cross-modal interpretation, and UAV flight planning.
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Agentic AI in Remote Sensing: Foundations, Taxonomy, and Emerging Systems.
NA Talemi, J Boone, F Afghah
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, GeoCV Workshop, 2026.
arxiv /
CVF /
Video
We present the first comprehensive survey of agentic AI in remote sensing, defining a unified taxonomy of single- and multi-agent systems and outlining how planning, tool use, and memory enable autonomous geospatial intelligence beyond static models.
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DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models.
NA Talemi, H Kashiani, H Rajoli, F Afghah
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025.
arxiv /
ACM /
Poster
We propose a novel directional saliency-aware prompt learning framework designed to enhance the adaptability and generalization of vision-language models.
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FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing.
H Kashiani, NA Talemi , F Afghah
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
CVF /
IEEE /
Poster
We propose FreqDebias, a frequency debiasing framework that mitigates spectral bias in deepfake detection through Forgery Mixup augmentation and dual consistency regularization, improving cross-domain generalization.
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Style-Pro: Style-Guided Prompt Learning for Generalizable Vision-Language Models.
NA Talemi, H Kashiani, F Afghah
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.
arxiv /
CVF /
IEEE /
Poster
We propose a style-guided prompt learning framework to enhance generalization in Vision-Language models.
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ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift.
H Kashiani, NA Talemi , F Afghah
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.
arxiv /
CVF /
IEEE /
Poster
We propose a robust multi-class anomaly detection framework with a class-aware prompt integration mechanism to mitigate inter-class interference and a domain adapter to handle domain shifts.
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CATFace: Cross-Attribute-Guided Transformer With Self-Attention Distillation for Low-Quality Face Recognition.
NA Talemi, H Kashiani, NM Nasrabadi
IEEE Transactions on Biometrics, Behavior, and Identity Science, 2024.
arxiv /
IEEE /
bibtex
We propose a novel multi-branch neural network with cross-attribute-guided fusion and self-attention distillation, improving face recognition in low-quality images using soft biometric attributes.
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AAFACE: Attribute-aware Attentional Network for Face Recognition.
NA Talemi , H Kashiani, and 4 more authors
IEEE International Conference on Image Processing (ICIP), 2023.
arxiv /
IEEE /
bibtex /
Poster
We present a multi-branch network using attribute-aware integration to enhance face recognition through soft biometric prediction.
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Towards Generalizable Morph Attack Detection with Consistency Regularization.
H Kashiani, NA Talemi, NM Nasrabadi
IEEE International Joint Conference on Biometrics (IJCB), 2023.
arxiv /
IEEE /
bibtex /
Poster /
code
We propose consistency regularization to enhance the generalization of morph attack detection through morph-wise augmentations to enhance robustness against unseen morph attacks in biometric systems.
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Face Image Quality Vector Assessment for Biometrics Applications.
N Najafzadeh, H Kashiani, MSE Saadabadi, NA Talemi, and 2 more authors
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023.
CVF /
IEEE /
bibtex
This paper proposes a multi-task neural network that generates a face quality vector, including nuisance factors, offering improved performance and detailed feedback for face image quality assessment.
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Superpixel-based brain tumor segmentation in MR images using an extended local fuzzy active contour model.
NA Talemi, RPR Hasanzadeh
Multimedia Tools and Applications, 2021.
Springer /
bibtex
This paper introduces a novel region-based fuzzy active contour model, leveraging curve evolution techniques, for brain tumor segmentation in magnetic resonance images, effectively addressing challenges arising from noise and heterogeneity.
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