Yonghyun Jeong

According to our database1, Yonghyun Jeong authored at least 17 papers between 2020 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Exploiting Style Latent Flows for Generalizing Deepfake Detection Video Detection.
CoRR, 2024

One-Shot Structure-Aware Stylized Image Synthesis.
CoRR, 2024

Noise Map Guidance: Inversion with Spatial Context for Real Image Editing.
CoRR, 2024

Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis.
CoRR, 2024

2023
Scaling of Class-wise Training Losses for Post-hoc Calibration.
Proceedings of the International Conference on Machine Learning, 2023

2022
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

mToFNet: Object Anti-Spoofing with Mobile Time-of-Flight Data.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

FingerprintNet: Synthesized Fingerprints for Generated Image Detection.
Proceedings of the Computer Vision - ECCV 2022, 2022

Membership Feature Disentanglement Network.
Proceedings of the ASIA CCS '22: ACM Asia Conference on Computer and Communications Security, Nagasaki, Japan, 30 May 2022, 2022

Differentially Private Normalizing Flows for Synthetic Tabular Data Generation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

FrePGAN: Robust Deepfake Detection Using Frequency-Level Perturbations.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Self-supervised GAN Detector.
CoRR, 2021

FICGAN: Facial Identity Controllable GAN for De-identification.
CoRR, 2021

Toward Spatially Unbiased Generative Models.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
DoFNet: Depth of Field Difference Learning for Detecting Image Forgery.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial Nets.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020


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