Daniel Olmeda Reino

30 papers A* 6A 3Journal 16Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ACDC: The Adverse Conditions Dataset With Correspondences for Robust Semantic Driving Scene Perception. IEEE Trans. Pattern Anal. Mach. Intell. Christos Sakaridis, Haoran Wang, Ke Li, René Zurbrügg, Arpit Jadon, Wim Abbeloos, Daniel Olmeda Reino, Luc Van Gool, Dengxin Dai
2026	J	`jnl`	Ego: Embedding-Guided Personalization of Vision-Language Models. CoRR Soroush Seifi, Simon Gardier, Vaggelis Dorovatas, Daniel Olmeda Reino, Rahaf Aljundi
2025	J	`jnl`	Efficient Few-Shot Continual Learning in Vision-Language Models. CoRR Aristeidis Panos, Rahaf Aljundi, Daniel Olmeda Reino, Richard E. Turner
2025	J	`jnl`	Efficient Few-Shot Continual Learning in Vision-Language Models. Trans. Mach. Learn. Res. Aristeidis Panos, Rahaf Aljundi, Daniel Olmeda Reino, Richard E. Turner
2025	—	`conf`	MT-Occ: Single-View 3D Occupancy Prediction via Multi-task Distillation. DAGM GCPR Zhi Li, Rahaf Aljundi, Daniel Olmeda Reino, Bernt Schiele
2025	J	`jnl`	Personalization Toolkit: Training Free Personalization of Large Vision Language Models. CoRR Soroush Seifi, Vaggelis Dorovatas, Daniel Olmeda Reino, Rahaf Aljundi
2024	J	`jnl`	Annotation Free Semantic Segmentation with Vision Foundation Models. CoRR Soroush Seifi, Daniel Olmeda Reino, Fabien Despinoy, Rahaf Aljundi
2024	J	`jnl`	Imperfect Vision Encoders: Efficient and Robust Tuning for Vision-Language Models. CoRR Aristeidis Panos, Rahaf Aljundi, Daniel Olmeda Reino, Richard E. Turner
2024	A	`conf`	OOD Aware Supervised Contrastive Learning. WACV Soroush Seifi, Daniel Olmeda Reino, Nikolay Chumerin, Rahaf Aljundi
2024	—	`conf`	VRS-NeRF: Visual Relocalization with Sparse Neural Radiance Field. ECCV Workshops (23) Fei Xue, Ignas Budvytis, Daniel Olmeda Reino, Roberto Cipolla
2024	J	`jnl`	VRS-NeRF: Visual Relocalization with Sparse Neural Radiance Field. CoRR Fei Xue, Ignas Budvytis, Daniel Olmeda Reino, Roberto Cipolla
2023	A*	`conf`	Contrastive Classification and Representation Learning with Probabilistic Interpretation. AAAI Rahaf Aljundi, Yash Patel, Milan Sulc, Nikolay Chumerin, Daniel Olmeda Reino
2023	A*	`conf`	First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning. ICCV Aristeidis Panos, Yuriko Kobe, Daniel Olmeda Reino, Rahaf Aljundi, Richard E. Turner
2023	J	`jnl`	First Session Adaptation: A Strong Replay-Free Baseline for Class-Incremental Learning. CoRR Aristeidis Panos, Yuriko Kobe, Daniel Olmeda Reino, Rahaf Aljundi, Richard E. Turner
2023	J	`jnl`	OOD Aware Supervised Contrastive Learning. CoRR Soroush Seifi, Daniel Olmeda Reino, Nikolay Chumerin, Rahaf Aljundi
2022	—	`conf`	Continual Novelty Detection. CoLLAs Rahaf Aljundi, Daniel Olmeda Reino, Nikolay Chumerin, Richard E. Turner
2022	J	`jnl`	Contrastive Classification and Representation Learning with Probabilistic Interpretation. CoRR Rahaf Aljundi, Yash Patel, Milan Sulc, Daniel Olmeda Reino, Nikolay Chumerin
2022	A*	`conf`	Efficient Large-scale Localization by Global Instance Recognition. CVPR Fei Xue, Ignas Budvytis, Daniel Olmeda Reino, Roberto Cipolla
2022	A	`conf`	Identifying Wrongly Predicted Samples: A Method for Active Learning. WACV Rahaf Aljundi, Nikolay Chumerin, Daniel Olmeda Reino
2022	A	`conf`	Style2NeRF: An Unsupervised One-Shot NeRF for Semantic 3D Reconstruction. BMVC James Charles, Wim Abbeloos, Daniel Olmeda Reino, Roberto Cipolla
2021	J	`jnl`	Continual Novelty Detection. CoRR Rahaf Aljundi, Daniel Olmeda Reino, Nikolay Chumerin, Richard E. Turner
2021	A*	`conf`	Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers. CVPR Apratim Bhattacharyya, Daniel Olmeda Reino, Mario Fritz, Bernt Schiele
2021	J	`jnl`	Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers. CoRR Apratim Bhattacharyya, Daniel Olmeda Reino, Mario Fritz, Bernt Schiele
2021	—	`conf`	MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation. ICCVW Jonas Heylen, Mark De Wolf, Bruno Dawagne, Marc Proesmans, Luc Van Gool, Wim Abbeloos, Hazem Abdelkawy, Daniel Olmeda Reino
2021	J	`jnl`	MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation. CoRR Jonas Heylen, Mark De Wolf, Bruno Dawagne, Marc Proesmans, Luc Van Gool, Wim Abbeloos, Hazem Abdelkawy, Daniel Olmeda Reino
2021	—	`conf`	On the Road to Large-Scale 3D Monocular Scene Reconstruction using Deep Implicit Functions. ICCVW Thomas Roddick, Benjamin Biggs, Daniel Olmeda Reino, Roberto Cipolla
2021	A*	`conf`	Road Anomaly Detection by Partial Image Reconstruction with Segmentation Coupling. ICCV Tomas Vojir, Tomás Sipka, Rahaf Aljundi, Nikolay Chumerin, Daniel Olmeda Reino, Jiri Matas
2021	A*	`conf`	Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection. ICCV Farzaneh Rezaeianaran, Rakshith Shetty, Rahaf Aljundi, Daniel Olmeda Reino, Shanshan Zhang, Bernt Schiele
2021	J	`jnl`	Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection. CoRR Farzaneh Rezaeianaran, Rakshith Shetty, Rahaf Aljundi, Daniel Olmeda Reino, Shanshan Zhang, Bernt Schiele
2020	J	`jnl`	Identifying Wrongly Predicted Samples: A Method for Active Learning. CoRR Rahaf Aljundi, Nikolay Chumerin, Daniel Olmeda Reino

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.