Seong Joon Oh

Orcid: 0000-0002-8985-7689

According to our database1, Seong Joon Oh authored at least 58 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Do Deep Neural Network Solutions Form a Star Domain?
CoRR, 2024

Calibrating Large Language Models Using Their Generations Only.
CoRR, 2024

Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks.
CoRR, 2024

Pretrained Visual Uncertainties.
CoRR, 2024

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification.
CoRR, 2024

2023
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets.
IEEE Trans. Pattern Anal. Mach. Intell., 2023

Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models.
CoRR, 2023

Exploring Practitioner Perspectives On Training Data Attribution Explanations.
CoRR, 2023

Trustworthy Machine Learning.
CoRR, 2023

A Bayesian Perspective On Training Data Attribution.
CoRR, 2023

Playing repeated games with Large Language Models.
CoRR, 2023

ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Bayesian Approach To Analysing Training Data Attribution In Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProPILE: Probing Privacy Leakage in Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs.
Proceedings of the International Conference on Machine Learning, 2023

Scratching Visual Transformer's Back with Uniform Attention.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Neglected Free Lunch - Learning Image Classifiers Using Annotation Byproducts.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
SelecMix: Debiased Learning by Contradicting-pair Sampling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Dataset Condensation via Efficient Synthetic-Data Parameterization.
Proceedings of the International Conference on Machine Learning, 2022

Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective.
Proceedings of the Tenth International Conference on Learning Representations, 2022

ECCV Caption: Correcting False Negatives by Collecting Machine-and-Human-verified Image-Caption Associations for MS-COCO.
Proceedings of the Computer Vision - ECCV 2022, 2022

Weakly Supervised Semantic Segmentation using Out-of-Distribution Data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

ALP: Data Augmentation Using Lexicalized PCFGs for Few-Shot Text Classification.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Region-based dropout with attention prior for weakly supervised object localization.
Pattern Recognit., 2021

Neural Hybrid Automata: Learning Dynamics With Multiple Modes and Stochastic Transitions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights.
Proceedings of the 9th International Conference on Learning Representations, 2021

Keep CALM and Improve Visual Feature Attribution.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Rethinking Spatial Dimensions of Vision Transformers.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Re-Labeling ImageNet: From Single to Multi-Labels, From Global to Localized Labels.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Probabilistic Embeddings for Cross-Modal Retrieval.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Person Recognition in Personal Photo Collections.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

VideoMix: Rethinking Data Augmentation for Video Classification.
CoRR, 2020

Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets.
CoRR, 2020

Slowing Down the Weight Norm Increase in Momentum-based Optimizers.
CoRR, 2020

An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods.
CoRR, 2020

Reliable Fidelity and Diversity Metrics for Generative Models.
Proceedings of the 37th International Conference on Machine Learning, 2020

Learning De-biased Representations with Biased Representations.
Proceedings of the 37th International Conference on Machine Learning, 2020

On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Evaluating Weakly Supervised Object Localization Methods Right.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Towards Reverse-Engineering Black-Box Neural Networks.
Proceedings of the Explainable AI: Interpreting, 2019

Modeling Uncertainty with Hedged Instance Embeddings.
Proceedings of the 7th International Conference on Learning Representations, 2019

CutMix: Regularization Strategy to Train Strong Classifiers With Localizable Features.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

What Is Wrong With Scene Text Recognition Model Comparisons? Dataset and Model Analysis.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Image manipulation against learned models: privacy and security implications.
PhD thesis, 2018

Modeling Uncertainty with Hedged Instance Embedding.
CoRR, 2018

Sequential Attacks on Agents for Long-Term Adversarial Goals.
CoRR, 2018

Understanding and Controlling User Linkability in Decentralized Learning.
CoRR, 2018

Towards Reverse-Engineering Black-Box Neural Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

Natural and Effective Obfuscation by Head Inpainting.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
Whitening Black-Box Neural Networks.
CoRR, 2017

Person Recognition in Social Media Photos.
CoRR, 2017

Adversarial Image Perturbation for Privacy Protection A Game Theory Perspective.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Generating Descriptions with Grounded and Co-referenced People.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Exploiting Saliency for Object Segmentation from Image Level Labels.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
Demo: I-Pic: A Platform for Privacy-Compliant Image Capture.
Proceedings of the 14th Annual International Conference on Mobile Systems, 2016

I-Pic: A Platform for Privacy-Compliant Image Capture.
Proceedings of the 14th Annual International Conference on Mobile Systems, 2016

Faceless Person Recognition: Privacy Implications in Social Media.
Proceedings of the Computer Vision - ECCV 2016, 2016


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