Zerun Wang - RankMe

14 papers A* 3Journal 8Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Difficulty Controlled Diffusion Model for Synthesizing Effective Training Data. AAAI Zerun Wang, Jiafeng Mao, Xueting Wang, Toshihiko Yamasaki
2026	J	`jnl`	Mirai: Autoregressive Visual Generation Needs Foresight. CoRR Yonghao Yu, Lang Huang, Zerun Wang, Runyi Li, Toshihiko Yamasaki
2024	J	`jnl`	From Obstacle to Opportunity: Enhancing Semi-supervised Learning with Synthetic Data. CoRR Zerun Wang, Jiafeng Mao, Liuyu Xiang, Toshihiko Yamasaki
2024	—	`conf`	SCOMatch: Alleviating Overtrusting in Open-Set Semi-supervised Learning. ECCV (51) Zerun Wang, Liuyu Xiang, Lang Huang, Jiafeng Mao, Ling Xiao, Toshihiko Yamasaki
2024	J	`jnl`	SCOMatch: Alleviating Overtrusting in Open-set Semi-supervised Learning. CoRR Zerun Wang, Liuyu Xiang, Lang Huang, Jiafeng Mao, Ling Xiao, Toshihiko Yamasaki
2024	J	`jnl`	Training Data Synthesis with Difficulty Controlled Diffusion Model. CoRR Zerun Wang, Jiafeng Mao, Xueting Wang, Toshihiko Yamasaki
2023	—	`conf`	Model Distillation for Lane Detection on Car-Level Chips. CICAI (2) Zixiong Wei, Zerun Wang, Hui Chen, Tianyu Shao, Lihong Huang, Xiaoyun Kang, Xiang Tian
2023	J	`jnl`	Online Open-set Semi-supervised Object Detection via Semi-supervised Outlier Filtering. CoRR Zerun Wang, Ling Xiao, Liuyu Xiang, Zhaotian Weng, Toshihiko Yamasaki
2022	A*	`conf`	ReMoNet: Recurrent Multi-Output Network for Efficient Video Denoising. AAAI Liuyu Xiang, Jundong Zhou, Jirui Liu, Zerun Wang, Haidong Huang, Jie Hu, Jungong Han, Yuchen Guo, Guiguang Ding
2022	J	`jnl`	Towards real-time object detection in GigaPixel-level video. Neurocomputing Kai Chen, Zerun Wang, Xueyang Wang, Dahan Gong, Longlong Yu, Yuchen Guo, Guiguang Ding
2021	J	`jnl`	LODE: Deep Local Deblurring and A New Benchmark. CoRR Zerun Wang, Liuyu Xiang, Fan Yang, Jinzhao Qian, Jie Hu, Haidong Huang, Jungong Han, Yuchen Guo, Guiguang Ding
2021	—	`conf`	The 2020 Low-Power Computer Vision Challenge. AICAS Xiao Hu, Ming-Ching Chang, Yuwei Chen, Rahul Sridhar, Zhenyu Hu, Yunhe Xue, Zhenyu Wu, Pengcheng Pi, Jiayi Shen, Jianchao Tan, Xiangru Lian, Ji Liu, Zhangyang Wang, Chia-Hsiang Liu, Yu-Shin Han, Yuan-Yao Sung, Yi Lee, Kai-Chiang Wu, Wei-Xiang Guo, Rick Lee, Shengwen Liang, Zerun Wang, Guiguang Ding, Gang Zhang, Teng Xi, Yubei Chen, Han Cai, Ligeng Zhu, Zhekai Zhang, Song Han, Seonghwan Jeong, YoungMin Kwon, Tianzhe Wang, Jeffery Pan
2020	A*	`conf`	PANDA: A Gigapixel-Level Human-Centric Video Dataset. CVPR Xueyang Wang, Xiya Zhang, Yinheng Zhu, Yuchen Guo, Xiaoyun Yuan, Liuyu Xiang, Zerun Wang, Guiguang Ding, David J. Brady, Qionghai Dai, Lu Fang
2020	J	`jnl`	PANDA: A Gigapixel-level Human-centric Video Dataset. CoRR Xueyang Wang, Xiya Zhang, Yinheng Zhu, Yuchen Guo, Xiaoyun Yuan, Liuyu Xiang, Zerun Wang, Guiguang Ding, David J. Brady, Qionghai Dai, Lu Fang

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.