Daeho Um - RankMe

22 papers A* 8B 1Journal 10Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Finding Optimal Video Moment without Training: Gaussian Boundary Optimization for Weakly Supervised Video Grounding. CoRR Sunoh Kim, Kimin Yun, Daeho Um
2025	J	`jnl`	Can AI Recognize the Style of Art? Analyzing Aesthetics through the Lens of Style Transfer. CoRR Yunha Yeo, Daeho Um
2025	B	`conf`	Enhancing Weakly Supervised Video Grounding via Diverse Inference Strategies for Boundary and Prediction Selection. AVSS Sunoh Kim, Daeho Um
2025	J	`jnl`	Enhancing Weakly Supervised Video Grounding via Diverse Inference Strategies for Boundary and Prediction Selection. CoRR Sunoh Kim, Daeho Um
2025	J	`jnl`	Leveraging Generative AI Models to Explore Human Identity. CoRR Yunha Yeo, Daeho Um
2025	A*	`conf`	PRIME: Deep Imbalanced Regression with Proxies. ICML Jongin Lim, Sucheol Lee, Daeho Um, Sung-Un Park, Jinwoo Shin
2025	A*	`conf`	Propagate and Inject: Revisiting Propagation-Based Feature Imputation for Graphs with Partially Observed Features. ICML Daeho Um, Sunoh Kim, Jiwoong Park, Jongin Lim, Seong-Jin Ahn, Seulki Park
2025	A*	`conf`	Relation-Aware Diffusion for Heterogeneous Graphs with Partially Observed Features. ICLR Daeho Um, Yoonji Lee, Jiwoong Park, Seulki Park, Yuneil Yeo, Seong-Jin Ahn
2025	A*	`conf`	Spreading Out-of-Distribution Detection on Graphs. ICLR Daeho Um, Jongin Lim, Sunoh Kim, Yuneil Yeo, Yoonho Jung
2025	J	`jnl`	The Butterfly Effect: Color-Guided Image Generation From Unconditional Diffusion Models. IEEE Access Yunha Yeo, Daeho Um
2024	A*	`conf`	Gene-Gene Relationship Modeling Based on Genetic Evidence for Single-Cell RNA-Seq Data Imputation. NeurIPS Daeho Um, Ji Won Yoon, Seong-Jin Ahn, Yunha Yeo
2024	A*	`conf`	Learnable Negative Proposals Using Dual-Signed Cross-Entropy Loss for Weakly Supervised Video Moment Localization. ACM Multimedia Sunoh Kim, Daeho Um, Hyunjun Choi, Jin Young Choi
2024	—	`conf`	MarUCOD: Unknown but Concerned Object Detection in Maritime Environments. ICPR (17) Hajung Yoon, Yoonji Lee, Hwijun Lee, Daeho Um, Hong Seok Choi, Jin Young Choi
2024	—	`conf`	RoCOCO: Robustness Benchmark of MS-COCO to Stress-Test Image-Text Matching Models. ECCV Workshops (20) Seulki Park, Daeho Um, Hajung Yoon, Sanghyuk Chun, Sangdoo Yun
2024	—	`conf`	Unseen Road Type Detection in Road Networks for Intelligent Transportation Systems. ITSC Daeho Um, Yuneil Yeo, Ji Won Yoon, Jin Young Choi
2023	A*	`conf`	Confidence-Based Feature Imputation for Graphs with Partially Known Features. ICLR Daeho Um, Jiwoong Park, Seulki Park, Jin Young Choi
2023	J	`jnl`	Confidence-Based Feature Imputation for Graphs with Partially Known Features. CoRR Daeho Um, Jiwoong Park, Seulki Park, Jin Young Choi
2023	J	`jnl`	RoCOCO: Robust Benchmark MS-COCO to Stress-test Robustness of Image-Text Matching Models. CoRR Seulki Park, Daeho Um, Hajung Yoon, Sanghyuk Chun, Sangdoo Yun, Jin Young Choi
2023	J	`jnl`	X-MAS: Extremely Large-Scale Multi-Modal Sensor Dataset for Outdoor Surveillance in Real Environments. IEEE Robotics Autom. Lett. DongKi Noh, Changki Sung, Taeyoung Uhm, Wooju Lee, Hyungtae Lim, Jaeseok Choi, Kyuewang Lee, Dasol Hong, Daeho Um, Inseop Chung, Hochul Shin, Min-Jung Kim, Hyoung-Rock Kim, Seungmin Baek, Hyun Myung
2022	J	`jnl`	X-MAS: Extremely Large-Scale Multi-Modal Sensor Dataset for Outdoor Surveillance in Real Environments. CoRR DongKi Noh, Changki Sung, Taeyoung Uhm, Wooju Lee, Hyungtae Lim, Jaeseok Choi, Kyuewang Lee, Dasol Hong, Daeho Um, Inseop Chung, Hochul Shin, Min-Jung Kim, Hyoung-Rock Kim, Seungmin Baek, Hyun Myung
2021	A*	`conf`	Class-Attentive Diffusion Network for Semi-Supervised Classification. AAAI Jongin Lim, Daeho Um, Hyung Jin Chang, Dae Ung Jo, Jin Young Choi
2020	J	`jnl`	Class-Attentive Diffusion Network for Semi-Supervised Classification. CoRR Jongin Lim, Daeho Um, Hyung Jin Chang, Dae Ung Jo, Jin Young Choi

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.