| Unsupervised intra-domain adaptation for semantic segmentation through self-supervision F Pan, I Shin, F Rameau, S Lee, IS Kweon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 274 | 2020 |
| Image-to-image translation via group-wise deep whitening-and-coloring transformation W Cho, S Choi, DK Park, I Shin, J Choo Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 104 | 2019 |
| Two-phase Pseudo Label Densification for Self-training based Domain Adaptation I Shin, S Woo, P F, IS Kweon Proceedings of the European conference on computer vision (ECCV), 2020 | 62 | 2020 |
| Labor: Labeling only if required for domain adaptive semantic segmentation I Shin, DJ Kim, JW Cho, S Woo, K Park, IS Kweon Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 26 | 2021 |
| Discover, hallucinate, and adapt: Open compound domain adaptation for semantic segmentation K Park, S Woo, I Shin, IS Kweon Advances in Neural Information Processing Systems 33, 10869-10880, 2020 | 23 | 2020 |
| MM-TTA: multi-modal test-time adaptation for 3d semantic segmentation I Shin, YH Tsai, B Zhuang, S Schulter, B Liu, S Garg, IS Kweon, KJ Yoon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 9 | 2022 |
| UDA-COPE: unsupervised domain adaptation for category-level object pose estimation T Lee, BU Lee, I Shin, J Choe, U Shin, IS Kweon, KJ Yoon Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 9 | 2022 |
| Unsupervised domain adaptation for video semantic segmentation I Shin, K Park, S Woo, IS Kweon arXiv preprint arXiv:2107.11052, 2021 | 6 | 2021 |
| Learning representations by contrasting clusters while bootstrapping instances J Lee, H Lee, I Shin, J Bae, IS Kweon, J Choo | 1 | |
| Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation D Kim, M Seo, K Park, I Shin, S Woo, IS Kweon, DG Choi arXiv preprint arXiv:2303.09779, 2023 | | 2023 |
| MULTI-MODAL TEST-TIME ADAPTATION Y Tsai, B Zhuang, S Schulter, B Liu, S Garg, R Moslemi, I Shin US Patent App. 17/903,393, 2023 | | 2023 |
| Learning Classifiers of Prototypes and Reciprocal Points for Universal Domain Adaptation S Hur, I Shin, K Park, S Woo, IS Kweon Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | | 2023 |
| CD-TTA: Compound Domain Test-time Adaptation for Semantic Segmentation J Song, K Park, I Shin, S Woo, IS Kweon arXiv preprint arXiv:2212.08356, 2022 | | 2022 |
| MATE: Masked Autoencoders are Online 3D Test-Time Learners MJ Mirza, I Shin, W Lin, A Schriebl, K Sun, J Choe, H Possegger, ... arXiv preprint arXiv:2211.11432, 2022 | | 2022 |
| MATE: Masked Autoencoders are Online 3D Test-Time Learners M Jehanzeb Mirza, I Shin, W Lin, A Schriebl, K Sun, J Choe, H Possegger, ... arXiv e-prints, arXiv: 2211.11432, 2022 | | 2022 |
| Moving from 2D to 3D: volumetric medical image classification for rectal cancer staging J Lee, J Oh, I Shin, Y Kim, DK Sohn, T Kim, IS Kweon Medical Image Computing and Computer Assisted Intervention–MICCAI 2022: 25th …, 2022 | | 2022 |
| KAIST-MTMC: A New Large-Scale Multi-Target Multiple Camera Tracking Benchmark S Woo, K Park, I Shin, M Kim, J Yoon, H Cho, SM Choi, H Kim, IS Kweon | | |
| Buyu Liu3 Sparsh Garg3 In So Kweon1 Kuk-Jin Yoon1 1KAIST 2Phiar Technologies 3NEC Laboratories America I Shin, YH Tsai, B Zhuang, S Schulter | | |
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