Gyuseong Lee
Gyuseong Lee
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Improving sample quality of diffusion models using self-attention guidance
S Hong, G Lee, W Jang, S Kim
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
Conmatch: Semi-supervised learning with confidence-guided consistency regularization
J Kim, Y Min, D Kim, G Lee, J Seo, K Ryoo, S Kim
European Conference on Computer Vision, 674-690, 2022
Midms: Matching interleaved diffusion models for exemplar-based image translation
J Seo, G Lee, S Cho, J Lee, S Kim
Proceedings of the AAAI Conference on Artificial Intelligence 37 (2), 2191-2199, 2023
Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labels
J Kim, K Ryoo, J Seo, G Lee, D Kim, H Cho, S Kim
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models
G Kim, W Jang, G Lee, S Hong, J Seo, S Kim
Pattern Recognition, 2024
Diffusion Model for Dense Matching
J Nam, G Lee, S Kim, H Kim, H Cho, S Kim, S Kim
The Twelfth International Conference on Learning Representations, 2023
Towards Flexible Inductive Bias via Progressive Reparameterization Scheduling
Y Lee, G Lee, K Ryoo, H Go, J Park, S Kim
Computer Vision–ECCV 2022 Workshops: Tel Aviv, Israel, October 23–27, 2022 …, 2023
AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning
J Kim, K Ryoo, G Lee, S Cho, J Seo, D Kim, H Cho, S Kim
arXiv preprint arXiv:2201.10444, 2022
Domain Generalization Using Large Pretrained Models with Mixture-of-Adapters
G Lee, W Jang, JH Kim, J Jung, S Kim
arXiv preprint arXiv:2310.11031, 2023
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