Federico Raue - RankMe

76 papers A* 2A 5B 9C 1Misc 2Journal 40Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PRISM: Diversifying Dataset Distillation by Decoupling Architectural Priors. Trans. Mach. Learn. Res. Brian Bernhard Moser, Shalini Sarode, Federico Raue, Stanislav Frolov, Krzysztof Adamkiewicz, Arundhati S. Shanbhag, Joachim Folz, Tobias Christian Nauen, Andreas Dengel
2026	J	`jnl`	When Pretty Isn't Useful: Investigating Why Modern Text-to-Image Models Fail as Reliable Training Data Generators. CoRR Krzysztof Adamkiewicz, Brian B. Moser, Stanislav Frolov, Tobias Christian Nauen, Federico Raue, Andreas Dengel
2025	J	`jnl`	A Coreset Selection of Coreset Selection Literature: Introduction and Recent Advances. CoRR Brian B. Moser, Arundhati S. Shanbhag, Stanislav Frolov, Federico Raue, Joachim Folz, Andreas Dengel
2025	J	`jnl`	A Study in Dataset Distillation for Image Super-Resolution. CoRR Tobias Dietz, Brian B. Moser, Tobias Christian Nauen, Federico Raue, Stanislav Frolov, Andreas Dengel
2025	J	`jnl`	Diffusion Models, Image Super-Resolution, and Everything: A Survey. IEEE Trans. Neural Networks Learn. Syst. Brian B. Moser, Arundhati S. Shanbhag, Federico Raue, Stanislav Frolov, Sebastian Palacio, Andreas Dengel
2025	B	`conf`	Distill the Best, Ignore the Rest: A Study in Latent Dataset Distillation on Core-Sets. IJCNN Brian B. Moser, Federico Raue, Tobias Christian Nauen, Stanislav Frolov, Andreas Dengel
2025	A	`conf`	Dynamic Attention-Guided Diffusion for Image Super-Resolution. WACV Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
2025	J	`jnl`	ForAug: Recombining Foregrounds and Backgrounds to Improve Vision Transformer Training with Bias Mitigation. CoRR Tobias Christian Nauen, Brian B. Moser, Federico Raue, Stanislav Frolov, Andreas Dengel
2025	J	`jnl`	HyperCore: Coreset Selection under Noise via Hypersphere Models. CoRR Brian B. Moser, Arundhati S. Shanbhag, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Joachim Folz, Andreas Dengel
2025	J	`jnl`	PRISM: Diversifying Dataset Distillation by Decoupling Architectural Priors. CoRR Brian B. Moser, Shalini Sarode, Federico Raue, Stanislav Frolov, Krzysztof Adamkiewicz, Arundhati S. Shanbhag, Joachim Folz, Tobias Christian Nauen, Andreas Dengel
2025	J	`jnl`	SubZeroCore: A Submodular Approach with Zero Training for Coreset Selection. CoRR Brian B. Moser, Tobias Christian Nauen, Arundhati S. Shanbhag, Federico Raue, Stanislav Frolov, Joachim Folz, Andreas Dengel
2025	A	`conf`	Which Transformer to Favor: A Comparative Analysis of Efficiency in Vision Transformers. WACV Tobias Christian Nauen, Sebastian Palacio, Federico Raue, Andreas Dengel
2024	J	`jnl`	A Low-Resolution Image is Worth 1x1 Words: Enabling Fine Image Super-Resolution with Transformers and TaylorShift. CoRR Sanath Budakegowdanadoddi Nagaraju, Brian B. Moser, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Andreas Dengel
2024	—	`conf`	A Study in Dataset Pruning for Image Super-Resolution. ICANN (2) Brian B. Moser, Federico Raue, Andreas Dengel
2024	J	`jnl`	A Study in Dataset Pruning for Image Super-Resolution. CoRR Brian B. Moser, Federico Raue, Andreas Dengel
2024	J	`jnl`	Diffusion Models, Image Super-Resolution And Everything: A Survey. CoRR Brian B. Moser, Arundhati S. Shanbhag, Federico Raue, Stanislav Frolov, Sebastian Palacio, Andreas Dengel
2024	J	`jnl`	Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning. CoRR Brian B. Moser, Federico Raue, Tobias Christian Nauen, Stanislav Frolov, Andreas Dengel
2024	J	`jnl`	FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data. CoRR Ahmed Anwar, Brian B. Moser, Dayananda Herurkar, Federico Raue, Vinit Hegiste, Tatjana Legler, Andreas Dengel
2024	J	`jnl`	Federated Learning for Blind Image Super-Resolution. CoRR Brian B. Moser, Ahmed Anwar, Federico Raue, Stanislav Frolov, Andreas Dengel
2024	J	`jnl`	Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning. CoRR Arundhati S. Shanbhag, Brian B. Moser, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Andreas Dengel
2024	J	`jnl`	Latent Dataset Distillation with Diffusion Models. CoRR Brian B. Moser, Federico Raue, Sebastian Palacio, Stanislav Frolov, Andreas Dengel
2024	A	`conf`	SphereCraft: A Dataset for Spherical Keypoint Detection, Matching and Camera Pose Estimation. WACV Christiano Couto Gava, Yunmin Cho, Federico Raue, Sebastian Palacio, Alain Pagani, Andreas Dengel
2024	—	`conf`	Tab-Distillation: Impacts of Dataset Distillation on Tabular Data For Outlier Detection. ICAIF Dayananda Herurkar, Federico Raue, Andreas Dengel
2024	B	`conf`	Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-Resolution. IJCNN Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
2024	J	`jnl`	Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution. CoRR Brian B. Moser, Stanislav Frolov, Tobias Christian Nauen, Federico Raue, Andreas Dengel
2023	B	`conf`	Cross-Domain Transformation for Outlier Detection on Tabular Datasets. IJCNN Dayananda Herurkar, Timur Sattarov, Jörn Hees, Sebastian Palacio, Federico Raue, Andreas Dengel
2023	—	`conf`	DWA: Differential Wavelet Amplifier for Image Super-Resolution. ICANN (2) Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
2023	J	`jnl`	DWA: Differential Wavelet Amplifier for Image Super-Resolution. CoRR Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
2023	J	`jnl`	DartsReNet: Exploring new RNN cells in ReNet architectures. CoRR Brian B. Moser, Federico Raue, Jörn Hees, Andreas Dengel
2023	J	`jnl`	Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances. IEEE Trans. Pattern Anal. Mach. Intell. Brian B. Moser, Federico Raue, Stanislav Frolov, Sebastian Palacio, Jörn Hees, Andreas Dengel
2023	C	`conf`	Sequential Spatial Transformer Networks for Salient Object Classification. ICPRAM David Dembinsky, Fatemeh Azimi, Federico Raue, Jörn Hees, Sebastian Palacio, Andreas Dengel
2023	—	`conf`	SphereGlue: Learning Keypoint Matching on High Resolution Spherical Images. CVPR Workshops Christiano Couto Gava, Vishal Mukunda, Tewodros Habtegebrial, Federico Raue, Sebastian Palacio, Andreas Dengel
2023	J	`jnl`	Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-Resolution. CoRR Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
2023	J	`jnl`	YODA: You Only Diffuse Areas. An Area-Masked Diffusion Approach For Image Super-Resolution. CoRR Brian B. Moser, Stanislav Frolov, Federico Raue, Sebastian Palacio, Andreas Dengel
2022	Misc	`conf`	Audioclip: Extending Clip to Image, Text and Audio. ICASSP Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
2022	J	`jnl`	Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances. CoRR Brian B. Moser, Federico Raue, Stanislav Frolov, Jörn Hees, Sebastian Palacio, Andreas Dengel
2022	—	`conf`	Less is More: Proxy Datasets in NAS approaches. CVPR Workshops Brian B. Moser, Federico Raue, Jörn Hees, Andreas Dengel
2022	J	`jnl`	Less is More: Proxy Datasets in NAS approaches. CoRR Brian B. Moser, Federico Raue, Jörn Hees, Andreas Dengel
2022	A	`conf`	Self-supervised Test-time Adaptation on Video Data. WACV Fatemeh Azimi, Sebastian Palacio, Federico Raue, Jörn Hees, Luca Bertinetto, Andreas Dengel
2021	J	`jnl`	A Reinforcement Learning Approach for Sequential Spatial Transformer Networks. CoRR Fatemeh Azimi, Federico Raue, Jörn Hees, Andreas Dengel
2021	B	`conf`	ANP-W2V: Effects of Composition Methods for Embedding Adjective-Noun Pairs. IJCNN Dayananda Herurkar, Philipp Blandfort, Federico Raue, Jörn Hees, Andreas Dengel
2021	J	`jnl`	Adversarial Text-to-Image Synthesis: A Review. CoRR Stanislav Frolov, Tobias Hinz, Federico Raue, Jörn Hees, Andreas Dengel
2021	J	`jnl`	Adversarial text-to-image synthesis: A review. Neural Networks Stanislav Frolov, Tobias Hinz, Federico Raue, Jörn Hees, Andreas Dengel
2021	—	`conf`	AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style. GCPR Stanislav Frolov, Avneesh Sharma, Jörn Hees, Tushar Karayil, Federico Raue, Andreas Dengel
2021	J	`jnl`	AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style. CoRR Stanislav Frolov, Avneesh Sharma, Jörn Hees, Tushar Karayil, Federico Raue, Andreas Dengel
2021	J	`jnl`	AudioCLIP: Extending CLIP to Image, Text and Audio. CoRR Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
2021	Misc	`conf`	Combining Transformer Generators with Convolutional Discriminators. KI Ricard Durall, Stanislav Frolov, Jörn Hees, Federico Raue, Franz-Josef Pfreundt, Andreas Dengel, Janis Keuper
2021	B	`conf`	ESResNe(X)t-fbsp: Learning Robust Time-Frequency Transformation of Audio. IJCNN Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
2021	J	`jnl`	ESResNe(X)t-fbsp: Learning Robust Time-Frequency Transformation of Audio. CoRR Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
2021	—	`conf`	Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching. VISIGRAPP (4: VISAPP) Fatemeh Azimi, Stanislav Frolov, Federico Raue, Jörn Hees, Andreas Dengel
2021	—	`conf`	Rethinking RNN-Based Video Object Segmentation. VISIGRAPP (Revised Selected Papers) Fatemeh Azimi, Federico Raue, Jörn Hees, Andreas Dengel
2021	J	`jnl`	Spatial Transformer Networks for Curriculum Learning. CoRR Fatemeh Azimi, Jean-Francois Jacques Nicolas Nies, Sebastian Palacio, Federico Raue, Jörn Hees, Andreas Dengel
2020	—	`conf`	DartsReNet: Exploring New RNN Cells in ReNet Architectures. ICANN (1) Brian B. Moser, Federico Raue, Jörn Hees, Andreas Dengel
2020	B	`conf`	ESResNet: Environmental Sound Classification Based on Visual Domain Models. ICPR Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
2020	J	`jnl`	ESResNet: Environmental Sound Classification Based on Visual Domain Models. CoRR Andrey Guzhov, Federico Raue, Jörn Hees, Andreas Dengel
2020	J	`jnl`	Hybrid Sequence to Sequence Model for Video Object Segmentation. CoRR Fatemeh Azimi, Stanislav Frolov, Federico Raue, Jörn Hees, Andreas Dengel
2020	B	`conf`	P ≈ NP, at least in Visual Question Answering. ICPR Shailza Jolly, Sebastian Palacio, Joachim Folz, Federico Raue, Jörn Hees, Andreas Dengel
2020	J	`jnl`	P ≈ NP, at least in Visual Question Answering. CoRR Shailza Jolly, Sebastian Palacio, Joachim Folz, Federico Raue, Jörn Hees, Andreas Dengel
2020	B	`conf`	Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory. ICPR Fatemeh Azimi, Benjamin Bischke, Sebastian Palacio, Federico Raue, Jörn Hees, Andreas Dengel
2020	J	`jnl`	Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory. CoRR Fatemeh Azimi, Benjamin Bischke, Sebastian Palacio, Federico Raue, Jörn Hees, Andreas Dengel
2019	—	`conf`	A Reinforcement Learning Approach for Sequential Spatial Transformer Networks. ICANN (1) Fatemeh Azimi, Federico Raue, Jörn Hees, Andreas Dengel
2019	—	`conf`	Comparison Between U-Net and U-ReNet Models in OCR Tasks. ICANN (3) Brian B. Moser, Federico Raue, Jörn Hees, Andreas Dengel
2019	—	`conf`	Conditional GANs for Image Captioning with Sentiments. ICANN (4) Tushar Karayil, Asif Irfan, Federico Raue, Jörn Hees, Andreas Dengel
2019	B	`conf`	Fusion Strategies for Learning User Embeddings with Neural Networks. IJCNN Philipp Blandfort, Tushar Karayil, Federico Raue, Jörn Hees, Andreas Dengel
2019	J	`jnl`	Fusion Strategies for Learning User Embeddings with Neural Networks. CoRR Philipp Blandfort, Tushar Karayil, Federico Raue, Jörn Hees, Andreas Dengel
2018	—	`—`	Association Learning inspired by the Symbol Grounding Problem. Federico Raue
2018	—	`conf`	Reading Type Classification based on Generative Models and Bidirectional Long Short-Term Memory. IUI Workshops Seyyed Saleh Mozaffari Chanijani, Federico Raue, Saeid Dashti Hassanzadeh, Stefan Agne, Syed Saqib Bukhari, Andreas Dengel
2018	J	`jnl`	Symbol Grounding Association in Multimodal Sequences with Missing Elements. J. Artif. Intell. Res. Federico Raue, Andreas Dengel, Thomas M. Breuel, Marcus Liwicki
2018	A*	`conf`	What Do Deep Networks Like to See? CVPR Sebastian Palacio, Joachim Folz, Jörn Hees, Federico Raue, Damian Borth, Andreas Dengel
2018	J	`jnl`	What do Deep Networks Like to See? CoRR Sebastian Palacio, Joachim Folz, Jörn Hees, Federico Raue, Damian Borth, Andreas Dengel
2017	—	`conf`	Classless Association Using Neural Networks. ICANN (2) Federico Raue, Sebastian Palacio, Andreas Dengel, Marcus Liwicki
2016	—	`conf`	Symbolic Association Using Parallel Multilayer Perceptron. ICANN (2) Federico Raue, Sebastian Palacio, Thomas M. Breuel, Wonmin Byeon, Andreas Dengel, Marcus Liwicki
2015	A	`conf`	Parallel sequence classification using recurrent neural networks and alignment. ICDAR Federico Raue, Wonmin Byeon, Thomas M. Breuel, Marcus Liwicki
2015	A*	`conf`	Scene labeling with LSTM recurrent neural networks. CVPR Wonmin Byeon, Thomas M. Breuel, Federico Raue, Marcus Liwicki
2015	J	`jnl`	Symbol Grounding Association in Multimodal Sequences with Missing Elements. CoRR Federico Raue, Thomas M. Breuel, Andreas Dengel, Marcus Liwicki
2015	—	`conf`	Symbol Grounding in Multimodal Sequences using Recurrent Neural Networks. CoCo@NIPS Federico Raue, Wonmin Byeon, Thomas M. Breuel, Marcus Liwicki

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.