Zezhou Cheng - RankMe

36 papers A* 8Journal 23Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LabelAny3D: Label Any Object 3D in the Wild. CoRR Jin Yao, Radowan Mahmud Redoy, Sebastian G. Elbaum, Matthew B. Dwyer, Zezhou Cheng
2026	J	`jnl`	WildRayZer: Self-supervised Large View Synthesis in Dynamic Environments. CoRR Xuweiyi Chen, Wentao Zhou, Zezhou Cheng
2025	—	`conf`	E-BARF: Bundle Adjusting Neural Radiance Fields from a Moving Event Camera. CVPR Workshops Zhipeng Tang, Shifan Zhu, Zezhou Cheng, Donghyun Kim, Erik G. Learned-Miller
2025	J	`jnl`	Empowering Dynamic Urban Navigation with Stereo and Mid-Level Vision. CoRR Wentao Zhou, Xuweiyi Chen, Vignesh Rajagopal, Jeffrey Chen, Rohan Chandra, Zezhou Cheng
2025	J	`jnl`	Frame In-N-Out: Unbounded Controllable Image-to-Video Generation. CoRR Boyang Wang, Xuweiyi Chen, Matheus Gadelha, Zezhou Cheng
2025	J	`jnl`	Point-MoE: Towards Cross-Domain Generalization in 3D Semantic Segmentation via Mixture-of-Experts. CoRR Xuweiyi Chen, Wentao Zhou, Aruni RoyChowdhury, Zezhou Cheng
2025	A*	`conf`	Probing the Mid-level Vision Capabilities of Self-Supervised Learning. CVPR Xuweiyi Chen, Markus Marks, Zezhou Cheng
2025	J	`jnl`	SAB3R: Semantic-Augmented Backbone in 3D Reconstruction. CoRR Xuweiyi Chen, Tian Xia, Sihan Xu, Jianing Yang, Joyce Chai, Zezhou Cheng
2024	J	`jnl`	Learning 3D Representations from Procedural 3D Programs. CoRR Xuweiyi Chen, Zezhou Cheng
2024	—	`conf`	Machine Unlearning of Pre-trained Large Language Models. ACL (1) Jin Yao, Eli Chien, Minxin Du, Xinyao Niu, Tianhao Wang, Zezhou Cheng, Xiang Yue
2024	J	`jnl`	Machine Unlearning of Pre-trained Large Language Models. CoRR Jin Yao, Eli Chien, Minxin Du, Xinyao Niu, Tianhao Wang, Zezhou Cheng, Xiang Yue
2024	J	`jnl`	Open Vocabulary Monocular 3D Object Detection. CoRR Jin Yao, Hao Gu, Xuweiyi Chen, Jiayun Wang, Zezhou Cheng
2024	J	`jnl`	Probing the Mid-level Vision Capabilities of Self-Supervised Learning. CoRR Xuweiyi Chen, Markus Marks, Zezhou Cheng
2023	—	`conf`	Accidental Turntables: Learning 3D Pose by Watching Objects Turn. ICCV (Workshops) Zezhou Cheng, Matheus Gadelha, Subhransu Maji
2023	A*	`conf`	LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs. ICCV Zezhou Cheng, Carlos Esteves, Varun Jampani, Abhishek Kar, Subhransu Maji, Ameesh Makadia
2023	J	`jnl`	LU-NeRF: Scene and Pose Estimation by Synchronizing Local Unposed NeRFs. CoRR Zezhou Cheng, Carlos Esteves, Varun Jampani, Abhishek Kar, Subhransu Maji, Ameesh Makadia
2022	J	`jnl`	Accidental Turntables: Learning 3D Pose by Watching Objects Turn. CoRR Zezhou Cheng, Matheus Gadelha, Subhransu Maji
2022	J	`jnl`	Cross-Modal 3D Shape Generation and Manipulation. CoRR Zezhou Cheng, Menglei Chai, Jian Ren, Hsin-Ying Lee, Kyle Olszewski, Zeng Huang, Subhransu Maji, Sergey Tulyakov
2022	—	`conf`	Cross-modal 3D Shape Generation and Manipulation. ECCV (3) Zezhou Cheng, Menglei Chai, Jian Ren, Hsin-Ying Lee, Kyle Olszewski, Zeng Huang, Subhransu Maji, Sergey Tulyakov
2022	A*	`conf`	GANORCON: Are Generative Models Useful for Few-shot Segmentation? CVPR Oindrila Saha, Zezhou Cheng, Subhransu Maji
2022	—	`conf`	Improving Few-Shot Part Segmentation Using Coarse Supervision. ECCV (30) Oindrila Saha, Zezhou Cheng, Subhransu Maji
2022	J	`jnl`	Improving Few-Shot Part Segmentation using Coarse Supervision. CoRR Oindrila Saha, Zezhou Cheng, Subhransu Maji
2021	A*	`conf`	A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification. CVPR Jong-Chyi Su, Zezhou Cheng, Subhransu Maji
2021	J	`jnl`	A Realistic Evaluation of Semi-Supervised Learning for Fine-Grained Classification. CoRR Jong-Chyi Su, Zezhou Cheng, Subhransu Maji
2021	J	`jnl`	AI for conservation: learning to track birds with radar. XRDS Zezhou Cheng, Subhransu Maji, Daniel Sheldon
2021	J	`jnl`	GANORCON: Are Generative Models Useful for Few-shot Segmentation? CoRR Oindrila Saha, Zezhou Cheng, Subhransu Maji
2021	A*	`conf`	On Equivariant and Invariant Learning of Object Landmark Representations. ICCV Zezhou Cheng, Jong-Chyi Su, Subhransu Maji
2020	A*	`conf`	Detecting and Tracking Communal Bird Roosts in Weather Radar Data. AAAI Zezhou Cheng, Saadia Gabriel, Pankaj Bhambhani, Daniel Sheldon, Subhransu Maji, Andrew Laughlin, David Winkler
2020	J	`jnl`	Detecting and Tracking Communal Bird Roosts in Weather Radar Data. CoRR Zezhou Cheng, Saadia Gabriel, Pankaj Bhambhani, Daniel Sheldon, Subhransu Maji, Andrew Laughlin, David Winkler
2020	J	`jnl`	Unsupervised Discovery of Object Landmarks via Contrastive Learning. CoRR Zezhou Cheng, Jong-Chyi Su, Subhransu Maji
2019	A*	`conf`	A Bayesian Perspective on the Deep Image Prior. CVPR Zezhou Cheng, Matheus Gadelha, Subhransu Maji, Daniel Sheldon
2019	J	`jnl`	A Bayesian Perspective on the Deep Image Prior. CoRR Zezhou Cheng, Matheus Gadelha, Subhransu Maji, Daniel Sheldon
2017	J	`jnl`	Colorization Using Neural Network Ensemble. IEEE Trans. Image Process. Zezhou Cheng, Qingxiong Yang, Bin Sheng
2016	J	`jnl`	Deep Colorization. CoRR Zezhou Cheng, Qingxiong Yang, Bin Sheng
2016	J	`jnl`	Image saliency detection based on rectangular-wave spectrum analysis. Multim. Tools Appl. Yi Yang, Bin Sheng, Wen Wu, Zezhou Cheng, Ruimin Shen
2015	A*	`conf`	Deep Colorization. ICCV Zezhou Cheng, Qingxiong Yang, Bin Sheng

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.