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Kwangrok Ryoo
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2020 – today
- 2023
- [c4]Jaehoon Ko, Kyusun Cho, Daewon Choi, Kwangrok Ryoo, Seungryong Kim:
3D GAN Inversion with Pose Optimization. WACV 2023: 2966-2975 - [i7]Kwangrok Ryoo, Yeonsik Jo, Seungjun Lee, Mira Kim, Ahra Jo, Seung Hwan Kim, Seungryong Kim, Soonyoung Lee:
Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object Detection. CoRR abs/2312.13822 (2023) - 2022
- [c3]Jiwon Kim, Kwangrok Ryoo, Junyoung Seo, Gyuseong Lee, Daehwan Kim, Hansang Cho, Seungryong Kim:
Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labels. CVPR 2022: 19667-19677 - [c2]Jiwon Kim, Youngjo Min, Daehwan Kim, Gyuseong Lee, Junyoung Seo, Kwangrok Ryoo, Seungryong Kim:
ConMatch: Semi-supervised Learning with Confidence-Guided Consistency Regularization. ECCV (30) 2022: 674-690 - [c1]Yunsung Lee, Gyuseong Lee, Kwangrok Ryoo, Hyojun Go, Jihye Park, Seungryong Kim:
Towards Flexible Inductive Bias via Progressive Reparameterization Scheduling. ECCV Workshops (4) 2022: 706-720 - [i6]Jiwon Kim, Kwangrok Ryoo, Gyuseong Lee, Seokju Cho, Junyoung Seo, Daehwan Kim, Hansang Cho, Seungryong Kim:
AggMatch: Aggregating Pseudo Labels for Semi-Supervised Learning. CoRR abs/2201.10444 (2022) - [i5]Jiwon Kim, Kwangrok Ryoo, Junyoung Seo, Gyuseong Lee, Daehwan Kim, Hansang Cho, Seungryong Kim:
Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labels. CoRR abs/2203.16038 (2022) - [i4]Jiwon Kim, Youngjo Min, Daehwan Kim, Gyuseong Lee, Junyoung Seo, Kwangrok Ryoo, Seungryong Kim:
ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization. CoRR abs/2208.08631 (2022) - [i3]Yunsung Lee, Gyuseong Lee, Kwangrok Ryoo, Hyojun Go, Jihye Park, Seungryong Kim:
Towards Flexible Inductive Bias via Progressive Reparameterization Scheduling. CoRR abs/2210.01370 (2022) - [i2]Jaehoon Ko, Kyusun Cho, Daewon Choi, Kwangrok Ryoo, Seungryong Kim:
3D GAN Inversion with Pose Optimization. CoRR abs/2210.07301 (2022) - [i1]Daehwan Kim, Kwangrok Ryoo, Hansang Cho, Seungryong Kim:
SplitNet: Learnable Clean-Noisy Label Splitting for Learning with Noisy Labels. CoRR abs/2211.11753 (2022)
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