Deeply Supervised Flow-Based Generative Models

Inkyu Shin, Chenglin Yang, Liang-Chieh Chen

ICCV 2025

[ Paper | Project page | Code ]

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 ]

Image-to-image translation via group-wise deep whitening-and-coloring transformation

Wongwoong Cho, Sungha Choi, David Keetae Park, Inkyu Shin, Jaegul Choo

CVPR 2019 [Oral]

[ Paper | Code ]

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 ]

MaXTron: Mask Transformer with Trajectory Attention for Video Panoptic Segmentation

Ju He, Qihang Yu, Inkyu Shin, Xueqing Deng, Xiaohui Shen, Alan Yuille, Liang-Chieh Chen

TMLR 2024

[ Paper | Code ]

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 ]

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 ]

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 ]

MATE: Masked Autoencoders are Online 3D Test-Time Learners

Muhammad Jehanzeb Mirza*, Inkyu Shin*, Wei Lin*, Andreas Schriebl, Kunyang Sun, Jaesung Choe,

Horst Possegger, Mateusz Kozinski, In So Kweon, Kuk-Jin Yoon, Horst Bischof (*Equal contribution)

ICCV 2023

[ Paper | Code ]

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 ]

Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation

Daehan Kim*, Minseok Seo*, Kwanyong Park, Inkyu Shin, Sanghyun Woo

AAAI 2023

[ Paper ]

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 ]

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 ]

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 ]

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 ]

Unsupervised Domain Adaptation for Video Semantic Segmentation

Inkyu Shin*, Kwanyong Park*, Sanghyun Woo, In So Kweon (*Equal contribution)

arXiv

[ Paper ]

Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation

Kwanyong Park, Sanghyun Woo, Inkyu Shin, In So Kweon

NeurIPS 2020

[ Paper ]

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 ]

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 ]