Inseop Chung

Orcid: 0000-0002-7701-6639

According to our database1, Inseop Chung authored at least 14 papers between 2020 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Mitigating the Bias in the Model for Continual Test-Time Adaptation.
CoRR, 2024

2023
X-MAS: Extremely Large-Scale Multi-Modal Sensor Dataset for Outdoor Surveillance in Real Environments.
IEEE Robotics Autom. Lett., 2023

What, How, and When Should Object Detectors Update in Continually Changing Test Domains?
CoRR, 2023

Open Domain Generalization with a Single Network by Regularization Exploiting Pre-trained Features.
CoRR, 2023

Exploiting Inter-pixel Correlations in Unsupervised Domain Adaptation for Semantic Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2023

End-to-End Multi-Object Detection with a Regularized Mixture Model.
Proceedings of the International Conference on Machine Learning, 2023

2022
Sparse MDOD: Training End-to-End Multi-Object Detector without Bipartite Matching.
CoRR, 2022

Maximizing Cosine Similarity Between Spatial Features for Unsupervised Domain Adaptation in Semantic Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Personalized Keyword Spotting through Multi-task Learning.
Proceedings of the Interspeech 2022, 2022

Dummy Prototypical Networks for Few-Shot Open-Set Keyword Spotting.
Proceedings of the Interspeech 2022, 2022

Unsupervised Domain Adaptation for One-Stage Object Detector Using Offsets to Bounding Box.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Training Multi-Object Detector by Estimating Bounding Box Distribution for Input Image.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Feature Fusion for Online Mutual Knowledge Distillation.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Feature-map-level Online Adversarial Knowledge Distillation.
Proceedings of the 37th International Conference on Machine Learning, 2020


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