Publication

International Journal

Scale-aware Token-matching for Transformer-based Object Detector

Aecheon Jung, Sungeun Hong, and Yoonsuk Hyun, Pattern Recognition Letters, vol. 185, pp. 197-202, September  2024.

Transformer  Object Detection   Small Object

G-TRACE: Grouped Temporal Recalibration for Video Object Segmentation

Jiyun Kim, Jooho Kim, and Sungeun Hong, Image and Vision Computing (Q1), May  2024.

Video Object Segmentation   Attention   Memory Network

Elastic Modulus Prediction from Indentation Using Machine Learning: Considering Tip Geometric Imperfection

Jong-hyoung Kim, Dong-Yeob Kim, Junsang Lee, Soon Woo Kwon, Jongheon Kim, Seung-Kyun Kang, Sungeun Hong, and Young-Cheon Kim, Metals and Materials International (Q1), March 2024.

Indentation   Elastic Modules

Visual and tactile perception techniques for braille recognition

Byeong-Sun Park, Seong-Min Im, Hojun Lee, Young Tack Lee, Changjoo Nam, Sungeun Hong, and Min-gu Kim, Micro and Nano Systems Letters, vol. 11, no. 1, pp. 1-8, December 2023.

Multimodal Learning   Sensor Fusion   Tactile   Touch   Braille Recognition

Re-Aging GAN++: Temporally consistent transformation of faces in videos

Farkhod Makhmudkhujaev, Sungeun Hong, and In Kyu Park, IEEE Access, vol. 11, pp. 137377-137386, December 2023.

Face   Age Transformation  Video Processing

SegTex: A large scale synthetic face dataset for face recognition

Laudwika Ambardi, Sungeun Hong, and In Kyu Park, IEEE Access, vol. 11, pp. 131939-131949, November 2023.

Face    Synthetic Data  Segmentation

TL-ADA: transferable loss-based active domain adaptation

Kyeongtak Han, Youngeun Kim, Dongyoon Han, Hojun Lee, and Sungeun Hong, Neural Networks (Q1), February 2023. 

Active Domain Adaptation   Active Learning   Learning Loss

Adaptive graph adversarial networks for partial domain adaptation

Youngeun Kim and Sungeun Hong, IEEE Trans. on Circuits and Systems for Video Technology (Q1), vol. 32, no. 1, pp. 172-182, January 2022.

Domain Adaptation   Graph Neural Networks

Domain adaptation without source data

Youngeun Kim, Donghyeon Cho, Kyeongtak Han, Priyadarshini Panda, and Sungeun Hong, IEEE Trans. on Artificial Intelligence (TAI), vol. 2, no. 6, pp. 508-518, December 2021.

Domain Adaptation   Privacy   Source-Free

Self-supervised feature enhancement networks for small object detection in noisy images

Geonsoo Lee, Sungeun Hong (co-first author), and Donghyeon Cho, IEEE Signal Processing Letters, vol. 28, pp. 1026-1030, May 2021.

Object Detection   Small Object   Self-Supervised Learning

Towards privacy-preserving domain adaptation

Youngeun Kim, Donghyeon Cho, and Sungeun Hong, IEEE Signal Processing Letters, vol. 27, pp. 1675-1679, September 2020.

Domain Adaptation   Privacy

Attention-guided adaptation factors for unsupervised facial domain adaptation

Sungeun Hong and Jongbin Ryu, Electronics Letters, vol. 56, no. 16, pp. 816-818, August 2020.

 Domain Adaptation   Attention

Unsupervised face domain transfer for low-resolution face recognition

Sungeun Hong and Jongbin Ryu, IEEE Signal Processing Letters, vol. 27, pp. 156-160, December 2019.

Face   Domain Adaptation   Low-Resolution

D3: Recognizing dynamic scenes with deep dual descriptor based on key frames and key segments

Sungeun Hong, Jongbin Ryu, Woobin Im, and Hyun S. Yang, Neurocomputing (Q1), vol. 273, pp. 611-621, January 2018.

Dynamic Scene   Dynamic Texture   Key Frame

Not all frames are equal: aggregating salient features for dynamic texture classification

Sungeun Hong, Jongbin Ryu, and Hyun S. Yang, Multidimensional Systems and Signal Processing, vol. 29, pp. 279-298, January 2018.

Dynamic Texture   Feature Aggregation

Sorted consecutive local binary pattern for texture classification

Jongbin Ryu, Sungeun Hong, and Hyun S. Yang, IEEE Trans. on Image Processing (Q1), vol. 24, no. 7, pp. 2254-2265, July 2015.

Texture Classification   LBP   Rotation Invariant

Recursive Bayesian fire recognition using greedy margin-maximizing clustering

Sujung Bae, Sungeun Hong, Yeongjae Choi, and Hyun S. Yang, Machine Vision and Applications, vol. 24, pp. 1605-1621, November 2013. 

Fire Recognition   Beyesian   Clustering

AI & Media Lab (AIM Lab)


Office : 90313, International Hall, Sungkyunkwan University,
25-2 Sungkyunkwan-ro, Jongno-gu, Seoul 03063, Korea

Email : csehong@skku.edu   Web : aim.skku.edu   Tel : 02-740-1809