Joonhyun Jeong

According to our database, Joonhyun Jeong authored at least 12 papers between 2019 and 2024.

Collaborative distances:

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

2024

EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection.

Joonhyun Jeong, Beomyoung Kim, Joonsang Yu, Youngjoon Yoo

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

ProxyDet: Synthesizing Proxy Novel Classes via Classwise Mixup for Open-Vocabulary Object Detection.

Joonhyun Jeong, Geondo Park, Jayeon Yoo, Hyungsik Jung, Heesu Kim

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Hijacking Context in Large Multi-modal Models.

Joonhyun Jeong

CoRR, 2023

Observations on K-Image Expansion of Image-Mixing Augmentation.

Joonhyun Jeong, Sungmin Cha, Jongwon Choi, Sangdoo Yun, Taesup Moon, Youngjoon Yoo

IEEE Access, 2023

GeNAS: Neural Architecture Search with Better Generalization.

Joonhyun Jeong, Joonsang Yu, Geondo Park, Dongyoon Han, Youngjoon Yoo

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

The Devil is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation.

Beomyoung Kim, Joonhyun Jeong, Dongyoon Han, Sung Ju Hwang

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

2022

Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection.

Joonhyun Jeong, Beomyoung Kim, Joonsang Yu, Youngjoon Yoo

CoRR, 2022

A New Pointwise Convolution in Deep Neural Networks Through Extremely Fast and Non Parametric Transforms.

Joonhyun Jeong, Incheon Cho, Eunseop Shin, Sung-Ho Bae

IEEE Access, 2022

Dataset Condensation via Efficient Synthetic-Data Parameterization.

Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun Jeong, Jung-Woo Ha, Hyun Oh Song

Proceedings of the International Conference on Machine Learning, 2022

2021

Observations on K-image Expansion of Image-Mixing Augmentation for Classification.

Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo, Sangdoo Yun, Taesup Moon, Jongwon Choi

CoRR, 2021

2019

An Inter-Layer Weight Prediction and Quantization for Deep Neural Networks based on a Smoothly Varying Weight Hypothesis.

Kang-Ho Lee, Joonhyun Jeong, Sung-Ho Bae

CoRR, 2019

New pointwise convolution in Deep Neural Networks through Extremely Fast and Non Parametric Transforms.

Joonhyun Jeong, Sung-Ho Bae

CoRR, 2019