Yabin Zhang - RankMe

43 papers A* 10A 1Journal 27Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Knowledge Regularized Negative Feature Tuning of Vision-Language Models for Out-of-Distribution Detection. ACM Multimedia Wenjie Zhu, Yabin Zhang, Xin Jin, Wenjun Zeng, Lei Zhang
2025	J	`jnl`	Knowledge Regularized Negative Feature Tuning of Vision-Language Models for Out-of-Distribution Detection. CoRR Wenjie Zhu, Yabin Zhang, Xin Jin, Wenjun Zeng, Lei Zhang
2025	J	`jnl`	Point-DAE: Denoising Autoencoders for Self-Supervised Point Cloud Learning. IEEE Trans. Neural Networks Learn. Syst. Yabin Zhang, Jiehong Lin, Ruihuang Li, Kui Jia, Lei Zhang
2024	—	`conf`	Architecture-Agnostic Unsupervised Gradient Regularization for Parameter-Efficient Transfer Learning. ECCV Workshops (22) Wenjie Zhu, Yabin Zhang, Pengfei Wang, Xin Jin, Wenjun Zeng, Lei Zhang
2024	A*	`conf`	Dual Memory Networks: A Versatile Adaptation Approach for Vision-Language Models. CVPR Yabin Zhang, Wenjie Zhu, Hui Tang, Zhiyuan Ma, Kaiyang Zhou, Lei Zhang
2024	J	`jnl`	Dual Memory Networks: A Versatile Adaptation Approach for Vision-Language Models. CoRR Yabin Zhang, Wenjie Zhu, Hui Tang, Zhiyuan Ma, Kaiyang Zhou, Lei Zhang
2024	—	`conf`	LAPT: Label-Driven Automated Prompt Tuning for OOD Detection with Vision-Language Models. ECCV (72) Yabin Zhang, Wenjie Zhu, Chenhang He, Lei Zhang
2024	J	`jnl`	LAPT: Label-driven Automated Prompt Tuning for OOD Detection with Vision-Language Models. CoRR Yabin Zhang, Wenjie Zhu, Chenhang He, Lei Zhang
2024	—	`conf`	ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillation. ECCV (7) Zhiyuan Ma, Yuxiang Wei, Yabin Zhang, Xiangyu Zhu, Zhen Lei, Lei Zhang
2024	J	`jnl`	ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillation. CoRR Zhiyuan Ma, Yuxiang Wei, Yabin Zhang, Xiangyu Zhu, Zhen Lei, Lei Zhang
2023	J	`jnl`	Adversarial Style Augmentation for Domain Generalization. CoRR Yabin Zhang, Bin Deng, Ruihuang Li, Kui Jia, Lei Zhang
2023	A*	`conf`	DynaMask: Dynamic Mask Selection for Instance Segmentation. CVPR Ruihuang Li, Chenhang He, Shuai Li, Yabin Zhang, Lei Zhang
2023	J	`jnl`	DynaMask: Dynamic Mask Selection for Instance Segmentation. CoRR Ruihuang Li, Chenhang He, Shuai Li, Yabin Zhang, Lei Zhang
2023	A*	`conf`	MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequences. CVPR Chenhang He, Ruihuang Li, Yabin Zhang, Shuai Li, Lei Zhang
2023	J	`jnl`	MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequences. CoRR Chenhang He, Ruihuang Li, Yabin Zhang, Shuai Li, Lei Zhang
2023	J	`jnl`	One-Stage Visual Relationship Referring With Transformers and Adaptive Message Passing. IEEE Trans. Image Process. Hang Wang, Youtian Du, Yabin Zhang, Shuai Li, Lei Zhang
2023	A*	`conf`	SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentation. CVPR Ruihuang Li, Chenhang He, Yabin Zhang, Shuai Li, Liyi Chen, Lei Zhang
2023	J	`jnl`	SIM: Semantic-aware Instance Mask Generation for Box-Supervised Instance Segmentation. CoRR Ruihuang Li, Chenhang He, Yabin Zhang, Shuai Li, Liyi Chen, Lei Zhang
2023	A*	`conf`	VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical Representations. ICCV Jiehong Lin, Zewei Wei, Yabin Zhang, Kui Jia
2023	J	`jnl`	VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical Representations. CoRR Jiehong Lin, Zewei Wei, Yabin Zhang, Kui Jia
2022	A*	`conf`	Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation. CVPR Ruihuang Li, Shuai Li, Chenhang He, Yabin Zhang, Xu Jia, Lei Zhang
2022	J	`jnl`	Class-Balanced Pixel-Level Self-Labeling for Domain Adaptive Semantic Segmentation. CoRR Ruihuang Li, Shuai Li, Chenhang He, Yabin Zhang, Xu Jia, Lei Zhang
2022	A*	`conf`	Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization. CVPR Yabin Zhang, Minghan Li, Ruihuang Li, Kui Jia, Lei Zhang
2022	J	`jnl`	Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization. CoRR Yabin Zhang, Minghan Li, Ruihuang Li, Kui Jia, Lei Zhang
2022	J	`jnl`	Masked Surfel Prediction for Self-Supervised Point Cloud Learning. CoRR Yabin Zhang, Jiehong Lin, Chenhang He, Yongwei Chen, Kui Jia, Lei Zhang
2022	J	`jnl`	Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning. CoRR Yabin Zhang, Jiehong Lin, Ruihuang Li, Kui Jia, Lei Zhang
2022	A*	`conf`	TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition. NeurIPS Yongwei Chen, Rui Chen, Jiabao Lei, Yabin Zhang, Kui Jia
2022	J	`jnl`	TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition. CoRR Yongwei Chen, Rui Chen, Jiabao Lei, Yabin Zhang, Kui Jia
2022	J	`jnl`	Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice. IEEE Trans. Pattern Anal. Mach. Intell. Yabin Zhang, Bin Deng, Hui Tang, Lei Zhang, Kui Jia
2021	J	`jnl`	Gradual Domain Adaptation via Self-Training of Auxiliary Models. CoRR Yabin Zhang, Bin Deng, Kui Jia, Lei Zhang
2021	J	`jnl`	On Universal Black-Box Domain Adaptation. CoRR Bin Deng, Yabin Zhang, Hui Tang, Changxing Ding, Kui Jia
2021	J	`jnl`	Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners. CoRR Yabin Zhang, Haojian Zhang, Bin Deng, Shuai Li, Kui Jia, Lei Zhang
2021	A	`conf`	Unsupervised Domain Adaptation of Black-Box Source Models. BMVC Haojian Zhang, Yabin Zhang, Kui Jia, Lei Zhang
2021	J	`jnl`	Unsupervised Domain Adaptation of Black-Box Source Models. CoRR Haojian Zhang, Yabin Zhang, Kui Jia, Lei Zhang
2020	J	`jnl`	Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation. CoRR Yabin Zhang, Bin Deng, Kui Jia, Lei Zhang
2020	—	`conf`	Label Propagation with Augmented Anchors: A Simple Semi-supervised Learning Baseline for Unsupervised Domain Adaptation. ECCV (4) Yabin Zhang, Bin Deng, Kui Jia, Lei Zhang
2020	J	`jnl`	Part-Aware Fine-Grained Object Categorization Using Weakly Supervised Part Detection Network. IEEE Trans. Multim. Yabin Zhang, Kui Jia, Zhixin Wang
2020	J	`jnl`	Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice. CoRR Yabin Zhang, Bin Deng, Hui Tang, Lei Zhang, Kui Jia
2019	A*	`conf`	Domain-Symmetric Networks for Adversarial Domain Adaptation. CVPR Yabin Zhang, Hui Tang, Kui Jia, Mingkui Tan
2019	J	`jnl`	Domain-Symmetric Networks for Adversarial Domain Adaptation. CoRR Yabin Zhang, Hui Tang, Kui Jia, Mingkui Tan
2018	—	`conf`	Fine-Grained Visual Categorization Using Meta-learning Optimization with Sample Selection of Auxiliary Data. ECCV (8) Yabin Zhang, Hui Tang, Kui Jia
2018	J	`jnl`	Fine-Grained Visual Categorization using Meta-Learning Optimization with Sample Selection of Auxiliary Data. CoRR Yabin Zhang, Hui Tang, Kui Jia
2018	J	`jnl`	Part-Aware Fine-grained Object Categorization using Weakly Supervised Part Detection Network. CoRR Yabin Zhang, Kui Jia, Zhixin Wang

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.