Yalong Jiang - RankMe

29 papers A* 1A 2B 3C 1Misc 3Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From Abstract Events to Grounded Cues: Cue-Guided Vision-Language Anomaly Detection. IEEE Signal Process. Lett. Yalong Jiang, Lian Huai, Yuyu Liu, Xingqun Jiang
2025	J	`jnl`	CLIP-TNseg: A Multi-Modal Hybrid Framework for Thyroid Nodule Segmentation in Ultrasound Images. IEEE Signal Process. Lett. Xinjie Sun, Boxiong Wei, Yalong Jiang, Liquan Mao, Qi Zhao
2025	A*	`conf`	Local Patterns Generalize Better for Novel Anomalies. ICLR Yalong Jiang
2025	B	`conf`	MGFA-Unet: A Lightweight Crack Segmentation Network for Crowdsourcing. ICPADS Nan Jiang, Tongtong Zhou, Zhixiang Qian, Lihong Tong, Yalong Jiang
2025	J	`jnl`	The Spatiotemporal Prediction Model of Urban Carbon Emissions Based on Graph Neural Networks. Int. J. Inf. Technol. Syst. Approach Wen Zhao, Yalong Jiang
2024	J	`jnl`	CLIP-TNseg: A Multi-Modal Hybrid Framework for Thyroid Nodule Segmentation in Ultrasound Images. CoRR Xinjie Sun, Boxiong Wei, Yalong Jiang, Liquan Mao, Qi Zhao
2024	J	`jnl`	Multi-Person Pose Tracking With Sparse Key-Point Flow Estimation and Hierarchical Graph Distance Minimization. IEEE Trans. Image Process. Yalong Jiang, Wenrui Ding, Hongguang Li, Zheru Chi
2024	J	`jnl`	Progressive prediction: Video anomaly detection via multi-grained prediction. IET Image Process. Xianlin Zeng, Yalong Jiang, Yufeng Wang, Qiang Fu, Wenrui Ding
2024	J	`jnl`	Reasonable Anomaly Detection Based on Long-Term Sequence Modeling. IEEE Trans. Circuits Syst. Video Technol. Yalong Jiang, Changkang Li, Wenrui Ding, Jinzhi Xiang, Zheru Chi
2024	A	`conf`	VLAVAD: Vision-Language Models Assisted Unsupervised Video Anomaly Detection. BMVC Changkang Li, Yalong Jiang
2024	J	`jnl`	Vision-Language Models Assisted Unsupervised Video Anomaly Detection. CoRR Yalong Jiang, Liquan Mao
2023	J	`jnl`	A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos. IEEE Trans. Circuits Syst. Video Technol. Xianlin Zeng, Yalong Jiang, Wenrui Ding, Hongguang Li, Yafeng Hao, Zifeng Qiu
2023	Misc	`conf`	A Physically Explainable Framework for Human-Related Anomaly Detection. ICASSP Yalong Jiang, Huining Li, Changkang Li
2023	J	`jnl`	An Approach for Multi-Object Tracking with Two-Stage Min-Cost Flow. CoRR Huining Li, Yalong Jiang, Xianlin Zeng, Feng Li, Zhipeng Wang
2023	J	`jnl`	Reasonable Anomaly Detection in Long Sequences. CoRR Yalong Jiang, Changkang Li
2023	J	`jnl`	Video Pose Track with Graph-Guided Sparse Motion Estimation. CoRR Yalong Jiang, Wenrui Ding, Hongguang Li, Zheru Chi
2022	Misc	`conf`	Binary Dense Predictors for Human Pose Estimation Based on Dynamic Thresholds and Filtering. ICASSP Xingrun Xing, Yalong Jiang, Baochang Zhang, Wenrui Ding, Yangguang Li, Hongguang Li, Huan Peng
2022	J	`jnl`	Tiny Vehicle Detection for Mid-to-High Altitude UAV Images Based on Visual Attention and Spatial-Temporal Information. Sensors Ruonan Yu, Hongguang Li, Yalong Jiang, Baochang Zhang, Yufeng Wang
2022	—	`conf`	Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies. ECCV (11) Xingrun Xing, Yangguang Li, Wei Li, Wenrui Ding, Yalong Jiang, Yufeng Wang, Jing Shao, Chunlei Liu, Xianglong Liu
2022	J	`jnl`	Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies. CoRR Xingrun Xing, Yangguang Li, Wei Li, Wenrui Ding, Yalong Jiang, Yufeng Wang, Jing Shao, Chunlei Liu, Xianglong Liu
2021	J	`jnl`	A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos. CoRR Xianlin Zeng, Yalong Jiang, Wenrui Ding, Hongguang Li, Yafeng Hao, Zifeng Qiu
2021	J	`jnl`	Lightweight Detection Network Based on Sub-Pixel Convolution and Objectness-Aware Structure for UAV Images. Sensors Xuanye Li, Hongguang Li, Yalong Jiang, Meng Wang
2020	—	`conf`	A Self-supervised Framework for Human Instance Segmentation. ECCV Workshops (2) Yalong Jiang, Wenrui Ding, Hongguang Li, Hua Yang, Xu Wang
2020	B	`conf`	Cam-Net: Compressed Attentive Multi-Granularity Network For Dynamic Scene Classification. ICIP Yue Li, Wenrui Ding, Yanjun Zhu, Yuanjun Huang, Yalong Jiang, Baochang Zhang
2019	J	`jnl`	A CNN Model for Semantic Person Part Segmentation With Capacity Optimization. IEEE Trans. Image Process. Yalong Jiang, Zheru Chi
2018	C	`conf`	A Novel Structure of Convolutional Layers with a Higher Performance-Complexity Ratio for Semantic Segmentation. ICARCV Yalong Jiang, Zheru Chi
2018	A	`conf`	Person Part Segmentation based on Weak Supervision. BMVC Yalong Jiang, Zheru Chi
2017	Misc	`conf`	A Fully-Convolutional Framework for Semantic Segmentation. DICTA Yalong Jiang, Zheru Chi
2017	B	`conf`	A scale-invariant framework for image classification with deep learning. SMC Yalong Jiang, Zheru Chi

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.