Zehua Sheng - RankMe

15 papers A* 4B 1Journal 10

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Learning Arbitrary-Scale RAW Image Downscaling with Wavelet-based Recurrent Reconstruction. ACM Multimedia Yang Ren, Hai Jiang, Wei Li, Menglong Yang, Heng Zhang, Zehua Sheng, Qingsheng Ye, Shuaicheng Liu
2025	J	`jnl`	Learning Arbitrary-Scale RAW Image Downscaling with Wavelet-based Recurrent Reconstruction. CoRR Yang Ren, Hai Jiang, Wei Li, Menglong Yang, Heng Zhang, Zehua Sheng, Qingsheng Ye, Shuaicheng Liu
2025	J	`jnl`	SGDFormer: One-stage transformer-based architecture for cross-spectral stereo image guided denoising. Inf. Fusion Runmin Zhang, Zhu Yu, Zehua Sheng, Jiacheng Ying, Si-Yuan Cao, Shu-Jie Chen, Bailin Yang, Junwei Li, Hui-Liang Shen
2025	J	`jnl`	STARNet: Low-light video enhancement using spatio-temporal consistency aggregation. Pattern Recognit. Zhe Wu, Zehua Sheng, Xue Zhang, Si-Yuan Cao, Runmin Zhang, Beinan Yu, Chenghao Zhang, Bailin Yang, Hui-Liang Shen
2025	J	`jnl`	TFDet: Target-Aware Fusion for RGB-T Pedestrian Detection. IEEE Trans. Neural Networks Learn. Syst. Xue Zhang, Xiaohan Zhang, Jiangtao Wang, Jiacheng Ying, Zehua Sheng, Heng Yu, Chunguang Li, Hui-Liang Shen
2024	J	`jnl`	SGDFormer: One-stage Transformer-based Architecture for Cross-Spectral Stereo Image Guided Denoising. CoRR Runmin Zhang, Zhu Yu, Zehua Sheng, Jiacheng Ying, Si-Yuan Cao, Shu-Jie Chen, Bailin Yang, Junwei Li, Hui-Liang Shen
2023	A*	`conf`	Aggregating Feature Point Cloud for Depth Completion. ICCV Zhu Yu, Zehua Sheng, Zili Zhou, Lun Luo, Si-Yuan Cao, Hong Gu, Huaqi Zhang, Hui-Liang Shen
2023	J	`jnl`	CMENet: A Cross-Modal Enhancement Network for Tobacco Leaf Grading. IEEE Access Qinglin He, Xiaobing Zhang, Jianxin Hu, Zehua Sheng, Qi Li, Si-Yuan Cao, Hui-Liang Shen
2023	J	`jnl`	Frequency-Domain Deep Guided Image Denoising. IEEE Trans. Multim. Zehua Sheng, Xiongwei Liu, Si-Yuan Cao, Hui-Liang Shen, Huaqi Zhang
2023	J	`jnl`	Guided Colorization Using Mono-Color Image Pairs. IEEE Trans. Image Process. Zehua Sheng, Hui-Liang Shen, Bo-Wen Yao, Huaqi Zhang
2023	A*	`conf`	Recurrent Homography Estimation Using Homography-Guided Image Warping and Focus Transformer. CVPR Si-Yuan Cao, Runmin Zhang, Lun Luo, Beinan Yu, Zehua Sheng, Junwei Li, Hui-Liang Shen
2023	J	`jnl`	Region-aware RGB and near-infrared image fusion. Pattern Recognit. Jiacheng Ying, Can Tong, Zehua Sheng, Bo-Wen Yao, Si-Yuan Cao, Heng Yu, Hui-Liang Shen
2023	A*	`conf`	Structure Aggregation for Cross-Spectral Stereo Image Guided Denoising. CVPR Zehua Sheng, Zhu Yu, Xiongwei Liu, Si-Yuan Cao, Yuqi Liu, Hui-Liang Shen, Huaqi Zhang
2023	J	`jnl`	TFDet: Target-aware Fusion for RGB-T Pedestrian Detection. CoRR Xue Zhang, Xiaohan Zhang, Zehua Sheng, Hui-Liang Shen
2022	B	`conf`	Frequency-Relevant Residual Learning for Multi-Modal Image Denoising. ICIP Xiongwei Liu, Zehua Sheng, Hui-Liang Shen

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.