Feifan Lv

12 papers A* 4A 2Journal 6

Year	Rank	Type	Title / Venue / Authors
2023	A	`conf`	Joint Low-light Enhancement and Super Resolution with Image Underexposure Level Guidance. BMVC Mingjie Xu, Chaoqun Zhuang, Feifan Lv, Feng Lu
2021	J	`jnl`	Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset. Int. J. Comput. Vis. Feifan Lv, Yu Li, Feng Lu
2020	A*	`conf`	An Integrated Enhancement Solution for 24-Hour Colorful Imaging. AAAI Feifan Lv, Yinqiang Zheng, Yicheng Li, Feng Lu
2020	J	`jnl`	An Integrated Enhancement Solution for 24-hour Colorful Imaging. CoRR Feifan Lv, Yinqiang Zheng, Yicheng Li, Feng Lu
2020	A*	`conf`	Fast Enhancement for Non-Uniform Illumination Images using Light-weight CNNs. ACM Multimedia Feifan Lv, Bo Liu, Feng Lu
2020	J	`jnl`	Fast Enhancement for Non-Uniform Illumination Images using Light-weight CNNs. CoRR Feifan Lv, Bo Liu, Feng Lu
2019	J	`jnl`	Attention-guided Low-light Image Enhancement. CoRR Feifan Lv, Feng Lu
2019	A*	`conf`	Pathological Evidence Exploration in Deep Retinal Image Diagnosis. AAAI Yuhao Niu, Lin Gu, Feng Lu, Feifan Lv, Zongji Wang, Imari Sato, Zijian Zhang, Yangyan Xiao, Xunzhang Dai, Tingting Cheng
2019	J	`jnl`	Real-Time Semantic Segmentation via Multiply Spatial Fusion Network. CoRR Haiyang Si, Zhiqiang Zhang, Feifan Lv, Gang Yu, Feng Lu
2019	A*	`conf`	Turn a Silicon Camera Into an InGaAs Camera. CVPR Feifan Lv, Yinqiang Zheng, Bohan Zhang, Feng Lu
2018	A	`conf`	MBLLEN: Low-Light Image/Video Enhancement Using CNNs. BMVC Feifan Lv, Feng Lu, Jianhua Wu, Chongsoon Lim
2018	J	`jnl`	Pathological Evidence Exploration in Deep Retinal Image Diagnosis. CoRR Yuhao Niu, Lin Gu, Feng Lu, Feifan Lv, Zongji Wang, Imari Sato, Zijian Zhang, Yangyan Xiao, Xunzhang Dai, Tingting Cheng

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.