Inkyu Shin

Orcid: 0009-0007-4314-9170

According to our database1, Inkyu Shin authored at least 18 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark.
CoRR, 2024

Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023
Test-Time Adaptation in the Dynamic World With Compound Domain Knowledge Management.
IEEE Robotics Autom. Lett., November, 2023

MaXTron: Mask Transformer with Trajectory Attention for Video Panoptic Segmentation.
CoRR, 2023

Learning Classifiers of Prototypes and Reciprocal Points for Universal Domain Adaptation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

MATE: Masked Autoencoders are Online 3D Test-Time Learners.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
CD-TTA: Compound Domain Test-time Adaptation for Semantic Segmentation.
CoRR, 2022

Moving from 2D to 3D: Volumetric Medical Image Classification for Rectal Cancer Staging.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

MM-TTA: Multi-Modal Test-Time Adaptation for 3D Semantic Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Unsupervised Domain Adaptation for Video Semantic Segmentation.
CoRR, 2021

LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Two-Phase Pseudo Label Densification for Self-training Based Domain Adaptation.
Proceedings of the Computer Vision - ECCV 2020, 2020

Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Image-To-Image Translation via Group-Wise Deep Whitening-And-Coloring Transformation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019


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