Faceless Person Recognition: Privacy Implications in Social Media. - Seong Joon Oh; Rodrigo Benenson; Mario Fritz; Bernt Schiele (ECCV (3), 2016)

I-Pic: A Platform for Privacy-Compliant Image Capture. - Paarijaat Aditya; Rijurekha Sen; Peter Druschel; Seong Joon Oh; Rodrigo Benenson; Mario Fritz; Bernt Schiele; Bobby Bhattacharjee; Tong Tong Wu (MobiSys, 2016)

Demo: I-Pic: A Platform for Privacy-Compliant Image Capture. - Paarijaat Aditya; Rijurekha Sen; Peter Druschel; Seong Joon Oh; Rodrigo Benenson; Mario Fritz; Bernt Schiele; Bobby Bhattacharjee; Tong Tong Wu (MobiSys (Companion Volume), 2016)

Exploiting Saliency for Object Segmentation from Image Level Labels. - Seong Joon Oh; Rodrigo Benenson; Anna Khoreva; Zeynep Akata; Mario Fritz; Bernt Schiele (CVPR, 2017)

Generating Descriptions with Grounded and Co-referenced People. - Anna Rohrbach; Marcus Rohrbach; Siyu Tang 001; Seong Joon Oh; Bernt Schiele (CVPR, 2017)

Adversarial Image Perturbation for Privacy Protection A Game Theory Perspective. - Seong Joon Oh; Mario Fritz; Bernt Schiele (ICCV, 2017)

Person Recognition in Social Media Photos. - Seong Joon Oh; Rodrigo Benenson; Mario Fritz; Bernt Schiele (CoRR, 2017)

Whitening Black-Box Neural Networks. - Seong Joon Oh; Max Augustin; Bernt Schiele; Mario Fritz (CoRR, 2017)

Natural and Effective Obfuscation by Head Inpainting. - Qianru Sun; Liqian Ma; Seong Joon Oh; Luc Van Gool; Bernt Schiele; Mario Fritz (CVPR, 2018)

Towards Reverse-Engineering Black-Box Neural Networks. - Seong Joon Oh; Max Augustin; Mario Fritz; Bernt Schiele (ICLR (Poster), 2018)

Understanding and Controlling User Linkability in Decentralized Learning. - Tribhuvanesh Orekondy; Seong Joon Oh; Bernt Schiele; Mario Fritz (CoRR, 2018)

Sequential Attacks on Agents for Long-Term Adversarial Goals. - Edgar Tretschk; Seong Joon Oh; Mario Fritz (CoRR, 2018)

Modeling Uncertainty with Hedged Instance Embedding. - Seong Joon Oh; Kevin Murphy 002; Jiyan Pan; Joseph Roth; Florian Schroff; Andrew C. Gallagher (CoRR, 2018)

Image manipulation against learned models: privacy and security implications. - Seong Joon Oh (2018)

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis. - Jeonghun Baek; Geewook Kim; Junyeop Lee; Sungrae Park; Dongyoon Han; Sangdoo Yun; Seong Joon Oh; Hwalsuk Lee (ICCV, 2019)

CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features. - Sangdoo Yun; Dongyoon Han; Sanghyuk Chun; Seong Joon Oh; Youngjoon Yoo; Junsuk Choe (ICCV, 2019)

Modeling Uncertainty with Hedged Instance Embeddings. - Seong Joon Oh; Kevin P. Murphy; Jiyan Pan; Joseph Roth; Florian Schroff; Andrew C. Gallagher (ICLR (Poster), 2019)

Towards Reverse-Engineering Black-Box Neural Networks. - Seong Joon Oh; Bernt Schiele; Mario Fritz (Explainable AI, 2019)

Evaluating Weakly Supervised Object Localization Methods Right. - Junsuk Choe; Seong Joon Oh; Seungho Lee; Sanghyuk Chun; Zeynep Akata; Hyunjung Shim (CVPR, 2020)

On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention. - Junyeop Lee; Sungrae Park; Jeonghun Baek; Seong Joon Oh; Seonghyeon Kim; Hwalsuk Lee (CVPR Workshops, 2020)

Learning De-biased Representations with Biased Representations. - Hyojin Bahng; Sanghyuk Chun; Sangdoo Yun; Jaegul Choo; Seong Joon Oh (ICML, 2020)

Reliable Fidelity and Diversity Metrics for Generative Models. - Muhammad Ferjad Naeem; Seong Joon Oh; Youngjung Uh; Yunjey Choi; Jaejun Yoo 001 (ICML, 2020)

An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods. - Sanghyuk Chun; Seong Joon Oh; Sangdoo Yun; Dongyoon Han; Junsuk Choe; Youngjoon Yoo (CoRR, 2020)

Slowing Down the Weight Norm Increase in Momentum-based Optimizers. - Byeongho Heo; Sanghyuk Chun; Seong Joon Oh; Dongyoon Han; Sangdoo Yun; Youngjung Uh; Jung-Woo Ha 001 (CoRR, 2020)

Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets. - Junsuk Choe; Seong Joon Oh; Sanghyuk Chun; Zeynep Akata; Hyunjung Shim (CoRR, 2020)

VideoMix: Rethinking Data Augmentation for Video Classification. - Sangdoo Yun; Seong Joon Oh; Byeongho Heo; Dongyoon Han; Jinhyung Kim (CoRR, 2020)

Person Recognition in Personal Photo Collections. - Seong Joon Oh; Rodrigo Benenson; Mario Fritz; Bernt Schiele (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Probabilistic Embeddings for Cross-Modal Retrieval. - Sanghyuk Chun; Seong Joon Oh; Rafael Sampaio de Rezende; Yannis Kalantidis; Diane Larlus (CVPR, 2021)

Re-Labeling ImageNet: From Single to Multi-Labels, From Global to Localized Labels. - Sangdoo Yun; Seong Joon Oh; Byeongho Heo; Dongyoon Han; Junsuk Choe; Sanghyuk Chun (CVPR, 2021)

Rethinking Spatial Dimensions of Vision Transformers. - Byeongho Heo; Sangdoo Yun; Dongyoon Han; Sanghyuk Chun; Junsuk Choe; Seong Joon Oh (ICCV, 2021)

Keep CALM and Improve Visual Feature Attribution. - Jae-Myung Kim; Junsuk Choe; Zeynep Akata; Seong Joon Oh (ICCV, 2021)

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights. - Byeongho Heo; Sanghyuk Chun; Seong Joon Oh; Dongyoon Han; Sangdoo Yun; Gyuwan Kim; Youngjung Uh; Jung-Woo Ha 001 (ICLR, 2021)

Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions. - Michael Poli; Stefano Massaroli; Luca Scimeca; Sanghyuk Chun; Seong Joon Oh; Atsushi Yamashita; Hajime Asama; Jinkyoo Park; Animesh Garg (NeurIPS, 2021)

Region-based dropout with attention prior for weakly supervised object localization. - Junsuk Choe; Dongyoon Han; Sangdoo Yun; Jung-Woo Ha 001; Seong Joon Oh; Hyunjung Shim (Pattern Recognit., 2021)

ALP: Data Augmentation Using Lexicalized PCFGs for Few-Shot Text Classification. - Hazel H. Kim; Daecheol Woo; Seong Joon Oh; Jeong-Won Cha; Yo-Sub Han (AAAI, 2022)

Weakly Supervised Semantic Segmentation using Out-of-Distribution Data. - Jungbeom Lee; Seong Joon Oh; Sangdoo Yun; Junsuk Choe; Eunji Kim 002; Sungroh Yoon (CVPR, 2022)

ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO. - Sanghyuk Chun; Wonjae Kim; Song Park; Minsuk Chang; Seong Joon Oh (ECCV (8), 2022)

Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective. - Luca Scimeca; Seong Joon Oh; Sanghyuk Chun; Michael Poli; Sangdoo Yun (ICLR, 2022)

Dataset Condensation via Efficient Synthetic-Data Parameterization. - Jang-Hyun Kim; Jinuk Kim; Seong Joon Oh; Sangdoo Yun; Hwanjun Song; Joonhyun Jeong; Jung-Woo Ha 001; Hyun Oh Song (ICML, 2022)

SelecMix: Debiased Learning by Contradicting-pair Sampling. - Inwoo Hwang; Sangjun Lee; Yunhyeok Kwak; Seong Joon Oh; Damien Teney; Jin-Hwa Kim; Byoung-Tak Zhang (NeurIPS, 2022)

Neglected Free Lunch - Learning Image Classifiers Using Annotation Byproducts. - Dongyoon Han; Junsuk Choe; Seonghyeok Chun; John Joon Young Chung; Minsuk Chang; Sangdoo Yun; Jean Y. Song; Seong Joon Oh (ICCV, 2023)

Scratching Visual Transformer's Back with Uniform Attention. - Nam Hyeon-Woo; Kim Yu-Ji; Byeongho Heo; Dongyoon Han; Seong Joon Oh; Tae-Hyun Oh (ICCV, 2023)

Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs. - Michael Kirchhof; Enkelejda Kasneci; Seong Joon Oh (ICML, 2023)

ProPILE: Probing Privacy Leakage in Large Language Models. - Siwon Kim; Sangdoo Yun; Hwaran Lee; Martin Gubri; Sungroh Yoon; Seong Joon Oh (NeurIPS, 2023)

URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates. - Michael Kirchhof; Bálint Mucsányi; Seong Joon Oh; Enkelejda Kasneci (NeurIPS, 2023)

A Bayesian Approach To Analysing Training Data Attribution In Deep Learning. - Elisa Nguyen; Minjoon Seo; Seong Joon Oh (NeurIPS, 2023)

ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets. - Damien Teney; Yong Lin; Seong Joon Oh; Ehsan Abbasnejad (NeurIPS, 2023)

Playing repeated games with Large Language Models. - Elif Akata; Lion Schulz; Julian Coda-Forno; Seong Joon Oh; Matthias Bethge; Eric Schulz (CoRR, 2023)

A Bayesian Perspective On Training Data Attribution. - Elisa Nguyen; Minjoon Seo; Seong Joon Oh (CoRR, 2023)

Trustworthy Machine Learning. - Bálint Mucsányi; Michael Kirchhof; Elisa Nguyen; Alexander Rubinstein 002; Seong Joon Oh (CoRR, 2023)

Exploring Practitioner Perspectives On Training Data Attribution Explanations. - Elisa Nguyen; Evgenii Kortukov; Jean Y. Song; Seong Joon Oh (CoRR, 2023)

Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models. - Luca Scimeca; Alexander Rubinstein 002; Damien Teney; Seong Joon Oh; Armand Mihai Nicolicioiu; Yoshua Bengio (CoRR, 2023)

Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets. - Junsuk Choe; Seong Joon Oh; Sanghyuk Chun; Seungho Lee; Zeynep Akata; Hyunjung Shim (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification. - Martin Gubri; Dennis Ulmer; Hwaran Lee; Sangdoo Yun; Seong Joon Oh (ACL (Findings), 2024)

Calibrating Large Language Models Using Their Generations Only. - Dennis Ulmer; Martin Gubri; Hwaran Lee; Sangdoo Yun; Seong Joon Oh (ACL (1), 2024)

Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks. - Bálint Mucsányi; Michael Kirchhof; Seong Joon Oh (NeurIPS, 2024)

Pretrained Visual Uncertainties. - Michael Kirchhof; Mark Collier; Seong Joon Oh; Enkelejda Kasneci (CoRR, 2024)

Studying Large Language Model Behaviors Under Realistic Knowledge Conflicts. - Evgenii Kortukov; Alexander Rubinstein 002; Elisa Nguyen; Seong Joon Oh (CoRR, 2024)

Scalable Ensemble Diversification for OOD Generalization and Detection. - Alexander Rubinstein 002; Luca Scimeca; Damien Teney; Seong Joon Oh (CoRR, 2024)

Towards User-Focused Research in Training Data Attribution for Human-Centered Explainable AI. - Elisa Nguyen; Johannes Bertram; Evgenii Kortukov; Jean Y. Song; Seong Joon Oh (CoRR, 2024)

Overcoming Domain Limitations in Open-vocabulary Segmentation. - Dongjun Hwang; Seong Joon Oh; Junsuk Choe (CoRR, 2024)

Decoupled Finetuning for Domain Generalizable Semantic Segmentation. - Jaehyun Pahk; Donghyeon Kwon; Seong Joon Oh; Suha Kwak (ICLR, 2025)

Do Deep Neural Network Solutions Form a Star Domain? - Ankit Sonthalia; Alexander Rubinstein 002; Ehsan Abbasnejad; Seong Joon Oh (ICLR, 2025)

Intermediate Layer Classifiers for OOD generalization. - Arnas Uselis; Seong Joon Oh (ICLR, 2025)

Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models. - Haritz Puerto; Martin Gubri; Sangdoo Yun; Seong Joon Oh (NAACL (Findings), 2025)

Small object matters in weakly supervised object localization. - Dongjun Hwang; Seong Joon Oh; Junsuk Choe (Neurocomputing, 2025)

CLIP Behaves like a Bag-of-Words Model Cross-modally but not Uni-modally. - Darina Koishigarina; Arnas Uselis; Seong Joon Oh (CoRR, 2025)

DiCoTTA: Domain-invariant Learning for Continual Test-time Adaptation. - Sohyun Lee; Nayeong Kim; Juwon Kang; Seong Joon Oh; Suha Kwak (CoRR, 2025)

Are We Done with Object-Centric Learning? - Alexander Rubinstein 002; Ameya Prabhu; Matthias Bethge; Seong Joon Oh (CoRR, 2025)

Diffusion Classifiers Understand Compositionality, but Conditions Apply. - Yujin Jeong; Arnas Uselis; Seong Joon Oh; Anna Rohrbach (CoRR, 2025)

C-SEO Bench: Does Conversational SEO Work? - Haritz Puerto; Martin Gubri; Tommaso Green; Seong Joon Oh; Sangdoo Yun (CoRR, 2025)

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers. - Tommaso Green; Martin Gubri; Haritz Puerto; Sangdoo Yun; Seong Joon Oh (CoRR, 2025)

On the rankability of visual embeddings. - Ankit Sonthalia; Arnas Uselis; Seong Joon Oh (CoRR, 2025)

Does Data Scaling Lead to Visual Compositional Generalization? - Arnas Uselis; Andrea Dittadi; Seong Joon Oh (CoRR, 2025)

First Hallucination Tokens Are Different from Conditional Ones. - Jakob Snel; Seong Joon Oh (CoRR, 2025)