| CARVIEW |
I received Ph.D. degree in future vehicle (electrical engineering) from the Korea Advanced Institute of Science and Technology (KAIST), where I was co-advised by Prof. Kuk-Jin Yoon and Prof. In So Kweon.
My research and engineering focus is on architecting robust Video World Models as a foundational step toward multimodal AGI.
Contact
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dlsrbgg33 [at] gmail.com
Education
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Ph.D. in Future Vehicle Engineering, 2024
KAIST, Korea
MS in Future Vehicle Engineering, 2021
KAIST, Korea
BS in Future Vehicle Engineering, 2019
HYU, Korea
Research Experiences
- Luma AI, Palo Alto, CANov 2025 - Current
Research Scientist / Engineer - ByteDance / TikTok, San Jose, CAAug 2024 - Oct 2025
Research Scientist - ByteDance / TikTok, San Jose, CASep 2023 - Jan 2024
Research Intern, Mentors: Liang-Chieh Chen and Qihang Yu - Google Research, LA, CA (virtual)May 2022 - April 2023
Student Researcher Intern, Mentors: Liang-Chieh Chen and Jun Xie - NEC Laboratories America, Inc, San Jose, CA (virtual)May 2021 - Aug 2021
Research Intern, Mentor: Yi-Hsuan Tsai
Publications
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Drag4D: Align Your Motion with Text-Driven 3D Scene Generation
Minjun Kang*, Inkyu Shin*, Taeyeop Lee, In So Kweon, Kuk-Jin Yoon (*Equal contribution)
arxiv 2025
[ Paper ]
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SCORE: Scaling audio generation using Standardized COmposite REwards
Jaemin Jung*, Jaehun Kim*, Inkyu Shin, Joon Son Chung (*Equal contribution)
arxiv 2025
[ Paper | Project page ]
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Deeply Supervised Flow-Based Generative Models
Inkyu Shin, Chenglin Yang, Liang-Chieh Chen
ICCV 2025
[ Paper | Project page | Code ]
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Enhancing Temporal Consistency in Video Editing by Reconstructing Videos with 3D Gaussian Splatting
Inkyu Shin, Qihang Yu, Xiaohui Shen, In So Kweon, Kuk-Jin Yoon, Liang-Chieh Chen
TMLR 2025
[ Paper | Project page | Code ]
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MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark
Sanghyun Woo*, Kwanyong Park*, Inkyu Shin*, Myungchul Kim*, In So Kweon (*Equal contribution)
CVPR 2024
[ Paper | Project page | Dataset ]
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Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation
Inkyu Shin, Dahun Kim, Qihang Yu, Jun Xie, Hong-Seok Kim, Bradely Green
In So Kweon, Kuk-Jin Yoon, Liang-Chieh Chen
WACV 2024 [Oral]
*Also presented at CVPRW 2023 Workshop(T4V)
[ Paper | Code | Video Demo ]
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Test-time Adaptation in the Dynamic World with Compound Domain Knowledge Management
Junha Song, Kwanyong Park, Inkyu Shin, Sanghyun Woo, Chaoning Zhang, In So Kweon
RAL-ICRA 2024
[ Paper ]
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TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation
Taeyeop Lee, Jonathan Tremblay, Valts Blukis, Bowen Wen, Byeong-Uk Lee, Inkyu Shin, Stan Birchfield, In So Kweon, Kuk-Jin Yoon
CVPR 2023
[ Paper ]
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Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation
Daehan Kim*, Minseok Seo*, Kwanyong Park, Inkyu Shin, Sanghyun Woo
AAAI 2023
[ Paper ]
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Learning Classifiers of Prototypes and Reciprocal Points for Universal Domain Adaptation
Sungsu Hur, Inkyu Shin, Kwanyong Park, Sanghyun Woo, In So Kweon
WACV 2023
[ Paper ]
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MM-TTA: Multi-Modal Test-Time Adaptation for 3D Semantic Segmentation
Inkyu Shin, Yi-Hsuan Tsai, Bingbing Zhuang, Samuel Schulter, Buyu Liu, Sparsh Garg, In So Kweon, Kuk-Jin Yoon
CVPR 2022
[ Paper | Project page ]
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UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimation
Taeyeop Lee, Byeong-Uk Lee, Inkyu Shin, Jaesung Choe, Ukcheol Shin, In So Kweon, Kuk-Jin Yoon
CVPR 2022
[ Paper ]
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Moving from 2D to 3D: volumetric medical image classification for rectal cancer staging
Joohyung Lee*, Jieun Oh*, Inkyu Shin, You-sung Kim, Dae Kyung Sohn, Tae-sung Kim, In So Kweon (*Equal contribution)
MICCAI 2022
[ Paper ]
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LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
Inkyu Shin, Dong-Jin Kim, Jae Won Cho, Sanghyun Woo, Kwanyong Park, In So Kweon
ICCV 2021 [Oral]
[ Paper ]
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Unsupervised Domain Adaptation for Video Semantic Segmentation
Inkyu Shin*, Kwanyong Park*, Sanghyun Woo, In So Kweon (*Equal contribution)
arXiv
[ Paper ]
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Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation
Kwanyong Park, Sanghyun Woo, Inkyu Shin, In So Kweon
NeurIPS 2020
[ Paper ]
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Two-phase Pseudo Label Densification for Self-training based Domain Adaptation
Inkyu Shin, Sanghyun Woo, Fei Pan, In So Kweon
ECCV 2020
*Also presented at CVPR 2020 Workshop(VL3)
[ Paper ]
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Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
Fei Pan, Inkyu Shin, Francois Rameau, Seokju Lee, In So Kweon
CVPR 2020 [Oral]
[ Project page | Paper | Code ]
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Awards
- Qualcomm Innovation Award, Qualcomm: 2020, 2021, 2022
- Best MS Thesis Award, Future Vehicle in KAIST: 2021
Activities
Talks
- Title: "Boosting Deep Visual Generation: Inside and Beyond the Model" @ NVIDIA and Google, Sep 2025
- Title: "How to do AI Research?" @ CGCL, KAIST. Aug 2024
- Title: "Unsupervised Domain Adaptation" @ Naver Labs. Mar 2020
Conference Reviewer
- Computer Vision: CVPR (2022~), ICCV (2023~), ECCV (2024~), WACV(2024~)
- Machine Learning: NeurIPS (2021~), ICLR (2024~), ICML (2022~)
Journal Reviewer
- Transactions on Pattern Analysis and Machine Intelligence (TPAMI)