Gyeong-Moon Park

According to our database, Gyeong-Moon Park authored at least 34 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Fisheye Object Detection with Visual Prompting-Aided Fine-Tuning.

Minwoo Jeon, Gyeong-Moon Park, Hyoseok Hwang

Remote. Sens., June, 2024

Wav2NeRF: Audio-driven realistic talking head generation via wavelet-based NeRF.

Ah-Hyung Shin, Jae-Ho Lee, Jiwon Hwang, Yoonhyung Kim, Gyeong-Moon Park

Image Vis. Comput., 2024

Towards High-fidelity Head Blending with Chroma Keying for Industrial Applications.

Hah Min Lew, Sahng-Min Yoo, Hyunwoo Kang, Gyeong-Moon Park

CoRR, 2024

RADIO: Reference-Agnostic Dubbing Video Synthesis.

Dongyeun Lee, Chaewon Kim, Sangjoon Yu, Jaejun Yoo, Gyeong-Moon Park

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

GLAD: Global-Local View Alignment and Background Debiasing for Unsupervised Video Domain Adaptation with Large Domain Gap.

Hyogun Lee, Kyungho Bae, Seong Jong Ha, Yumin Ko, Gyeong-Moon Park, Jinwoo Choi

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

CED: Comparing Embedding Differences for Detecting Out-of-Distribution and Hallucinated Text.

Hakyung Lee, Keon-Hee Park, Hoyoon Byun, Jeyoon Yeom, Jihee Kim, Gyeong-Moon Park, Kyungwoo Song

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Online Continuous Generalized Category Discovery.

Keon-Hee Park, Hakyung Lee, Kyungwoo Song, Gyeong-Moon Park

Proceedings of the Computer Vision - ECCV 2024, 2024

Versatile Incremental Learning: Towards Class and Domain-Agnostic Incremental Learning.

Min-Yeong Park, Jae-Ho Lee, Gyeong-Moon Park

Proceedings of the Computer Vision - ECCV 2024, 2024

Towards Model-Agnostic Dataset Condensation by Heterogeneous Models.

Jun-Yeong Moon, Jung Uk Kim, Gyeong-Moon Park

Proceedings of the Computer Vision - ECCV 2024, 2024

Generative Unlearning for Any Identity.

Juwon Seo, Sung-Hoon Lee, Tae-Young Lee, Seungjun Moon, Gyeong-Moon Park

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Pre-trained Vision and Language Transformers are Few-Shot Incremental Learners.

Keon-Hee Park, Kyungwoo Song, Gyeong-Moon Park

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Open-Set Domain Adaptation for Semantic Segmentation.

Seun-An Choe, Ah-Hyung Shin, Keon-Hee Park, Jinwoo Choi, Gyeong-Moon Park

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era.

Chaoning Zhang, Chenshuang Zhang, Chenghao Li, Yu Qiao, Sheng Zheng, Sumit Kumar Dam, Mengchun Zhang, Jung Uk Kim, Seong Tae Kim, Jinwoo Choi, Gyeong-Moon Park, Sung-Ho Bae, Lik-Hang Lee, Pan Hui, In So Kweon, Choong Seon Hong

CoRR, 2023

Time Series Anomaly Detection Using Transformer-Based GAN With Two-Step Masking.

Ah-Hyung Shin, Seong Tae Kim, Gyeong-Moon Park

IEEE Access, 2023

LFS-GAN: Lifelong Few-Shot Image Generation.

Juwon Seo, Ji-Su Kang, Gyeong-Moon Park

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Online Class Incremental Learning on Stochastic Blurry Task Boundary via Mask and Visual Prompt Tuning.

Jun-Yeong Moon, Keon-Hee Park, Jung Uk Kim, Gyeong-Moon Park

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

LINe: Out-of-Distribution Detection by Leveraging Important Neurons.

Yong Hyun Ahn, Gyeong-Moon Park, Seong Tae Kim

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

SR-EM: Episodic Memory Aware of Semantic Relations Based on Hierarchical Clustering Resonance Network.

Jae-Woo Choi, Gyeong-Moon Park, Jong-Hwan Kim

IEEE Trans. Cybern., 2022

WaGI : Wavelet-based GAN Inversion for Preserving High-frequency Image Details.

Seung Jun Moon, Chaewon Kim, Gyeong-Moon Park

CoRR, 2022

IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion.

Seungjun Moon, Gyeong-Moon Park

CoRR, 2022

IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion.

Seung Jun Moon, Gyeong-Moon Park

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Convolutional Neural Network With Developmental Memory for Continual Learning.

Gyeong-Moon Park, Sahng-Min Yoo, Jong-Hwan Kim

IEEE Trans. Neural Networks Learn. Syst., 2021

Adaptive Developmental Resonance Network.

Gyeong-Moon Park, Jong-Hwan Kim

IEEE Trans. Neural Networks Learn. Syst., 2021

2020

Continual Unsupervised Domain Adaptation with Adversarial Learning.

Joonhyuk Kim, Sahng-Min Yoo, Gyeong-Moon Park, Jong-Hwan Kim

CoRR, 2020

Non-Probabilistic Cosine Similarity Loss for Few-Shot Image Classification.

Joonhyuk Kim, Inug Yoon, Gyeong-Moon Park, Jong-Hwan Kim

Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019

Developmental Resonance Network.

Gyeong-Moon Park, Jae-Woo Choi, Jong-Hwan Kim

IEEE Trans. Neural Networks Learn. Syst., 2019

Multi-channel Classification Resonance Network^*.

Joonhyuk Kim, Gyeong-Moon Park, Jong-Hwan Kim

Proceedings of the 7th International Conference on Robot Intelligence Technology and Applications, 2019

2018

Deep ART Neural Model for Biologically Inspired Episodic Memory and Its Application to Task Performance of Robots.

Gyeong-Moon Park, Yong-Ho Yoo, Deok-Hwa Kim, Jong-Hwan Kim

IEEE Trans. Cybern., 2018

2017

Task Intelligence of Robots: Neural Model-Based Mechanism of Thought and Online Motion Planning.

In-Bae Jeong, Woo-Ri Ko, Gyeong-Moon Park, Deok-Hwa Kim, Yong-Ho Yoo, Jong-Hwan Kim

IEEE Trans. Emerg. Top. Comput. Intell., 2017

Realization of task intelligence for service robots in an unstructured environment.

Deok-Hwa Kim, Gyeong-Moon Park, Yong-Ho Yoo, Si-Jung Ryu, In-Bae Jeong, Jong-Hwan Kim

Annu. Rev. Control., 2017

Context preference-based deep adaptive resonance theory: Integrating user preferences into episodic memory encoding and retrieval.

Dick Sigmund, Gyeong-Moon Park, Jong-Hwan Kim

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016

Biologically-inspired episodic memory model considering the context information.

Gyeong-Moon Park, Sanghyun Cho, Jong-Hwan Kim

Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016

Deep Adaptive Resonance Theory for learning biologically inspired episodic memory.

Gyeong-Moon Park, Jong-Hwan Kim

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2014

Falling Prevention System from External Disturbances for Humanoid Robots.

Gyeong-Moon Park, Seung-Hwan Baek, Jong-Hwan Kim

Proceedings of the Robot Intelligence Technology and Applications 3, 2014