Dahuin Jung

Orcid: 0000-0002-1344-1054

According to our database¹, Dahuin Jung authored at least 34 papers between 2018 and 2026.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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Links

On csauthors.net:

Bibliography

2026

FEAT: Fashion Editing and Try-On from Any Design.

[BibT_eX]

[DOI]

CoRR, May, 2026

LIBERO-Para: A Diagnostic Benchmark and Metrics for Paraphrase Robustness in VLA Models.

[BibT_eX]

[DOI]

CoRR, March, 2026

Balancing Saliency and Coverage: Semantic Prominence-Aware Budgeting for Visual Token Compression in VLMs.

[BibT_eX]

[DOI]

CoRR, March, 2026

Leveraging dynamic feature fusion of self & cross-attention for robust multimodal emotion recognition.

[BibT_eX]

[DOI]

ICT Express, 2026

2025

Harnessing consistency for improved test-time adaptation.

[BibT_eX]

[DOI]

Dahuin Jung

Image Vis. Comput., 2025

Diffusion-Stego: Training-free diffusion generative steganography via message projection.

[BibT_eX]

[DOI]

Inf. Sci., 2025

EntUn: Mitigating the forget-retain dilemma in unlearning via entropy.

[BibT_eX]

[DOI]

Dahuin Jung

ICT Express, 2025

Know "No" Better: A Data-Driven Approach for Enhancing Negation Awareness in CLIP.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

Disentangled Motion Modeling for Video Frame Interpolation.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Sample-efficient Adversarial Imitation Learning.

[BibT_eX]

[DOI]

Dahuin Jung

Hyungyu Lee

Sungroh Yoon

J. Mach. Learn. Res., 2024

Textual Training for the Hassle-Free Removal of Unwanted Visual Data.

[BibT_eX]

[DOI]

CoRR, 2024

Normality Addition via Normality Detection in Industrial Image Anomaly Detection Models.

[BibT_eX]

[DOI]

Jihun Yi

Dahuin Jung

Sungroh Yoon

CoRR, 2024

Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Efficient Diffusion-Driven Corruption Editor for Test-Time Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Real-world prediction of preclinical Alzheimer's disease with a deep generative model.

[BibT_eX]

[DOI]

Artif. Intell. Medicine, October, 2023

PixelSteganalysis: Pixel-Wise Hidden Information Removal With Low Visual Degradation.

[BibT_eX]

[DOI]

IEEE Trans. Dependable Secur. Comput., 2023

On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

CLeAR: Continual Learning on Algorithmic Reasoning for Human-like Intelligence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PUCA: Patch-Unshuffle and Channel Attention for Enhanced Self-Supervised Image Denoising.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improving Visual Prompt Tuning for Self-supervised Vision Transformers.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Probabilistic Concept Bottleneck Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

New Insights for the Stability-Plasticity Dilemma in Online Continual Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generating Instance-level Prompts for Rehearsal-free Continual Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Imbalanced Data Classification via Cooperative Interaction Between Classifier and Generator.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2022

FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 51st International Conference on Parallel Processing, 2022

Confidence Score for Source-Free Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Stein Latent Optimization for Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Stein Latent Optimization for GANs.

[BibT_eX]

[DOI]

CoRR, 2021

2020

AnomiGAN: Generative Adversarial Networks for Anonymizing Private Medical Data.

[BibT_eX]

[DOI]

Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

iCaps: An Interpretable Classifier via Disentangled Capsule Networks.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

AnomiGAN: Generative adversarial networks for anonymizing private medical data.

[BibT_eX]

[DOI]

Ho Bae

Dahuin Jung

Sungroh Yoon

CoRR, 2019

HexaGAN: Generative Adversarial Nets for Real World Classification.

[BibT_eX]

[DOI]

Uiwon Hwang

Dahuin Jung

Sungroh Yoon

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Security and Privacy Issues in Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Dahuin Jung

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