Streamable Neural Fields. - Junwoo Cho; Seungtae Nam; Daniel Rho; Jong Hwan Ko; Eunbyung Park (ECCV (20), 2022)

Separable PINN: Mitigating the Curse of Dimensionality in Physics-Informed Neural Networks. - Junwoo Cho; Seungtae Nam; Hyunmo Yang; Seok-Bae Yun; Youngjoon Hong; Eunbyung Park (CoRR, 2022)

Improvement in Object Detection Using Multi-Scale RoI Pooling and Feature Pyramid Network. - Seungtae Nam; Daeho Lee (J. Comput. Sci. Eng., 2022)

Masked Wavelet Representation for Compact Neural Radiance Fields. - Daniel Rho; Byeonghyeon Lee; Seungtae Nam; Joo Chan Lee; Jong Hwan Ko; Eunbyung Park (CVPR, 2023)

Separable Physics-Informed Neural Networks. - Junwoo Cho; Seungtae Nam; Hyunmo Yang; Seok-Bae Yun; Youngjoon Hong; Eunbyung Park (NeurIPS, 2023)

Mip-Grid: Anti-aliased Grid Representations for Neural Radiance Fields. - Seungtae Nam; Daniel Rho; Jong Hwan Ko; Eunbyung Park (NeurIPS, 2023)

FREQ-MIP-AA: Frequency Mip Representation for Anti-Aliasing Neural Radiance Fields. - Youngin Park; Seungtae Nam; Cheul-Hee Hahm; Eunbyung Park (ICIP, 2024)

Coordinate-Aware Modulation for Neural Fields. - Joo Chan Lee; Daniel Rho; Seungtae Nam; Jong Hwan Ko; Eunbyung Park (ICLR, 2024)

SelfSplat: Pose-Free and 3D Prior-Free Generalizable 3D Gaussian Splatting. - Gyeongjin Kang; Jisang Yoo; Jihyeon Park; Seungtae Nam; Hyeonsoo Im; Sangheon Shin; Sangpil Kim; Eunbyung Park (CVPR, 2025)

Generative Densification: Learning to Densify Gaussians for High-Fidelity Generalizable 3D Reconstruction. - Seungtae Nam; Xiangyu Sun; Gyeongjin Kang; Younggeun Lee; Seungjun Oh; Eunbyung Park (CVPR, 2025)

iLRM: An Iterative Large 3D Reconstruction Model. - Gyeongjin Kang; Seungtae Nam; Xiangyu Sun; Sameh Khamis; Abdelrahman Mohamed; Eunbyung Park (CoRR, 2025)