Checkerboard Dropout: A Structured Dropout With Checkerboard Pattern for Convolutional Neural Networks. - Khanh-Binh Nguyen; Jaehyuk Choi 001; Joon-Sung Yang (IEEE Access, 2022)

VSCHH 2023: A Benchmark for the View Synthesis Challenge of Human Heads. - Youngkyoon Jang; Jiali Zheng; Jifei Song; Helisa Dhamo; Eduardo Pérez-Pellitero; Thomas Tanay; Matteo Maggioni; Richard Shaw; Sibi Catley-Chandar; Yiren Zhou; Jiankang Deng; Ruijie Zhu 002; et al. (ICCV (Workshops), 2023)

Boosting Semi-Supervised Learning by bridging high and low-confidence predictions. - Khanh-Binh Nguyen; Joon-Sung Yang (ICCV (Workshops), 2023)

EUNNet: Efficient UN-Normalized Convolution Layer for Stable Training of Deep Residual Networks Without Batch Normalization Layer. - Khanh-Binh Nguyen; Jaehyuk Choi 001; Joon-Sung Yang (IEEE Access, 2023)

RETRO: Reusing teacher projection head for efficient embedding distillation on Lightweight Models via Self-supervised Learning. - Khanh-Binh Nguyen; Chae Jung Park (BMVC, 2024)

SequenceMatch Revisiting the design of weak-strong augmentations for Semi-supervised learning. - Khanh-Binh Nguyen (WACV, 2024)

Debiasing, calibrating, and improving Semi-supervised Learning performance via simple Ensemble Projector. - Khanh-Binh Nguyen (WACV, 2024)

SAVE: Segment Audio-Visual Easy way using Segment Anything Model. - Khanh-Binh Nguyen; Chae Jung Park (CoRR, 2024)

Symmetric masking strategy enhances the performance of Masked Image Modeling. - Khanh-Binh Nguyen; Chae Jung Park (CoRR, 2024)

On Calibration of Prompt Learning Using Temperature Scaling. - Khanh-Binh Nguyen; Chae Jung Park (IEEE Access, 2025)

Simplifying Masked Image Modeling With Symmetric Masking and Contrastive Learning. - Khanh-Binh Nguyen; Chae Jung Park (IEEE Access, 2025)