• Continual Learning: Forget-free Winning Subnetworks for Video Representations, 

Haeyong Kang, Jaehong Yoon, Sung Ju Hwang, and Chang D. Yoo

• Progressive Fourier Neural Representation for Sequential Video Compilation, 

Haeyong Kang, Jaehong Yoon, DaHyun Kim, Sung Ju Hwang, Chang D. Yoo,

ICLR2024, GitHub

• Skew Class-balanced Re-weighting for Unbiased Scene Graph Generation, 

Haeyong Kang and Chang D. Yoo,  

MAKE2023 (MAKE, Machine Learning and Knowledge Extraction),  GitHub

• Maximum Margin Learning of t-SPNs for Cell Classification With Filtered Input, 

Haeyong Kang, Chang D. Yoo, and Yongcheon Na, 

IJSTSP2016

• On the Soft-Subnetwork for Few-shot Class Incremental Learning, 

Haeyong Kang, Jaehong Yoon, Sultan R. H. Madjid, Sung Ju Hwang, and Chang D. Yoo, 

ICLR2023, GitHub

• Forget-free Continual Learning with Winning Subnetworks, 

Haeyong Kang, Rusty John Lloyd Mina, Sultan Rizky Hikmawan Madjid, Jaehong Yoon, Mark Hasegawa-Johnson, Sung Ju Hwang, and Chang D. Yoo, 

ICML2022, GitHub

• Semantic Grouping Network for Video Captioning, 

Hobin Ryu, Sunghun Kang, Haeyong Kang, and Chang D. Yoo, 

AAAI2021, GitHub 

• SCNet: Training Inference Sample Consistency for Instance Segmentation, 

Thang Vu, Haeyong Kang, and Chang D. Yoo, 

AAAI2021, GitHub

• Learning Imbalanced Datasets With Maximum Margin Loss, 

Haeyong Kang, Thang Vu, and Chang D. Yoo,  

ICIP2021, GitHub

• Sphererpn: Learning Spheres For High-Quality Region Proposals On 3d Point Clouds Object Detection, 

Thang Vu, Kookhoi Kim, Haeyong Kang, Xuan Thanh Nguyen, Tung M. Luu, and Chang D. Yoo,  

ICIP2021

• Few-Shot Associative Domain Adaptation for Surface Normal Estimation, 

Haeyong Kang, Gwangsu Kim, and Chang D. Yoo, 

 ICIP2019