Ramprasaath R. Selvaraju

29 papers A* 6A 3C 1Journal 16Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	A	`conf`	CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision. AISTATS Aman Shrivastava, Ramprasaath R. Selvaraju, Nikhil Naik, Vicente Ordonez
2023	A	`conf`	PreViTS: Contrastive Pretraining with Video Tracking Supervision. WACV Brian Chen, Ramprasaath R. Selvaraju, Shih-Fu Chang, Juan Carlos Niebles, Nikhil Naik
2022	—	`conf`	Can domain adaptation make object recognition work for everyone? CVPR Workshops Viraj Prabhu, Ramprasaath R. Selvaraju, Judy Hoffman, Nikhil Naik
2022	J	`jnl`	Can domain adaptation make object recognition work for everyone? CoRR Viraj Prabhu, Ramprasaath R. Selvaraju, Judy Hoffman, Nikhil Naik
2022	A	`conf`	TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation. BMVC Jun Wang, Mingfei Gao, Yuqian Hu, Ramprasaath R. Selvaraju, Chetan Ramaiah, Ran Xu, Joseph F. JáJá, Larry Davis
2022	J	`jnl`	TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation. CoRR Jun Wang, Mingfei Gao, Yuqian Hu, Ramprasaath R. Selvaraju, Chetan Ramaiah, Ran Xu, Joseph F. JáJá, Larry S. Davis
2021	A*	`conf`	Align before Fuse: Vision and Language Representation Learning with Momentum Distillation. NeurIPS Junnan Li, Ramprasaath R. Selvaraju, Akhilesh Gotmare, Shafiq R. Joty, Caiming Xiong, Steven Chu-Hong Hoi
2021	J	`jnl`	Align before Fuse: Vision and Language Representation Learning with Momentum Distillation. CoRR Junnan Li, Ramprasaath R. Selvaraju, Akhilesh Deepak Gotmare, Shafiq R. Joty, Caiming Xiong, Steven C. H. Hoi
2021	A*	`conf`	CASTing Your Model: Learning To Localize Improves Self-Supervised Representations. CVPR Ramprasaath R. Selvaraju, Karan Desai, Justin Johnson, Nikhil Naik
2021	J	`jnl`	CLIP-Lite: Information Efficient Visual Representation Learning from Textual Annotations. CoRR Aman Shrivastava, Ramprasaath R. Selvaraju, Nikhil Naik, Vicente Ordonez
2021	J	`jnl`	PreViTS: Contrastive Pretraining with Video Tracking Supervision. CoRR Brian Chen, Ramprasaath R. Selvaraju, Shih-Fu Chang, Juan Carlos Niebles, Nikhil Naik
2021	—	`conf`	SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency. NAACL-HLT Sameer Dharur, Purva Tendulkar, Dhruv Batra, Devi Parikh, Ramprasaath R. Selvaraju
2020	J	`jnl`	CASTing Your Model: Learning to Localize Improves Self-Supervised Representations. CoRR Ramprasaath R. Selvaraju, Karan Desai, Justin Johnson, Nikhil Naik
2020	J	`jnl`	Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization. Int. J. Comput. Vis. Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra
2020	J	`jnl`	SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency. CoRR Sameer Dharur, Purva Tendulkar, Dhruv Batra, Devi Parikh, Ramprasaath R. Selvaraju
2020	J	`jnl`	SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions. CoRR Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh, Eric Horvitz, Marco Ribeiro, Besmira Nushi, Ece Kamar
2020	A*	`conf`	SQuINTing at VQA Models: Introspecting VQA Models With Sub-Questions. CVPR Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh, Eric Horvitz, Marco Túlio Ribeiro, Besmira Nushi, Ece Kamar
2019	J	`jnl`	Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded. CoRR Ramprasaath R. Selvaraju, Stefan Lee, Yilin Shen, Hongxia Jin, Dhruv Batra, Devi Parikh
2019	C	`conf`	Trick or TReAT : Thematic Reinforcement for Artistic Typography. ICCC Purva Tendulkar, Kalpesh Krishna, Ramprasaath R. Selvaraju, Devi Parikh
2019	J	`jnl`	Trick or TReAT: Thematic Reinforcement for Artistic Typography. CoRR Purva Tendulkar, Kalpesh Krishna, Ramprasaath R. Selvaraju, Devi Parikh
2018	—	`conf`	Choose Your Neuron: Incorporating Domain Knowledge Through Neuron-Importance. ECCV (13) Ramprasaath R. Selvaraju, Prithvijit Chattopadhyay, Mohamed Elhoseiny, Tilak Sharma, Dhruv Batra, Devi Parikh, Stefan Lee
2018	J	`jnl`	Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance. CoRR Ramprasaath R. Selvaraju, Prithvijit Chattopadhyay, Mohamed Elhoseiny, Tilak Sharma, Dhruv Batra, Devi Parikh, Stefan Lee
2018	A*	`conf`	Diverse Beam Search for Improved Description of Complex Scenes. AAAI Ashwin K. Vijayakumar, Michael Cogswell, Ramprasaath R. Selvaraju, Qing Sun, Stefan Lee, David J. Crandall, Dhruv Batra
2017	A*	`conf`	Counting Everyday Objects in Everyday Scenes. CVPR Prithvijit Chattopadhyay, Ramakrishna Vedantam, Ramprasaath R. Selvaraju, Dhruv Batra, Devi Parikh
2017	A*	`conf`	Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization. ICCV Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, Dhruv Batra
2016	J	`jnl`	Counting Everyday Objects in Everyday Scenes. CoRR Prithvijit Chattopadhyay, Ramakrishna Vedantam, Ramprasaath R. Selvaraju, Dhruv Batra, Devi Parikh
2016	J	`jnl`	Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models. CoRR Ashwin K. Vijayakumar, Michael Cogswell, Ramprasaath R. Selvaraju, Qing Sun, Stefan Lee, David J. Crandall, Dhruv Batra
2016	J	`jnl`	Grad-CAM: Why did you say that? CoRR Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, Dhruv Batra
2016	J	`jnl`	Grad-CAM: Why did you say that? Visual Explanations from Deep Networks via Gradient-based Localization. CoRR Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, Dhruv Batra

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.