Seungjun Nah
Senior Research Scientist
NVIDIA
Publications | Datasets | CV
Publications (Selected)
- NVIDIA, “World Simulation with Video Foundation Models for Physical AI,” arXiv 2025. [arXiv] [website]
- NVIDIA, “Cosmos World Foundation Model Platform for Physical AI,” arXiv 2025. [arXiv] [website]
- NVIDIA, “Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models,” arXiv 2024. [arXiv] [website] [video]
- Songwei Ge, Seungjun Nah, Guilin Liu, Tyler Poon, Andrew Tao, Bryan Catanzaro, David Jacobs, Jia-Bin Huang, Ming-Yu Liu, Yogesh Balaji, “Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models,” ICCV 2023. [paper] [arXiv]
- Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Qinsheng Zhang, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, Tero Karras, and Ming-Yu Liu, “eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers,” arXiv 2022. [arXiv] [website]
- Cheeun Hong, Sungyong Baik, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee, “Content-Aware Dynamic Quantization for Image Super-Resolution,” ECCV 2022. [paper] [arXiv] [github]
- Junghun Oh, Heewon Kim, Seungjun Nah, Cheeun Hong, Jonghyun Choi, and Kyoung Mu Lee, “Attentive Fine-Grained Structured Sparsity for Image Restoration,” CVPR 2022 [paper][arXiv]
- Seungjun Nah, Sanghyun Son, Jaerin Lee, and Kyoung Mu Lee, “Clean Images are Hard to Reblur: Exploiting the Ill-Posed Inverse Task for Dynamic Scene Deblurring,” ICLR 2022 [paper] [presentation] [slides] [youtube] [poster]
- Joonkyu Park, Seungjun Nah, and Kyoung Mu Lee, “Recurrence-in-Recurrence Networks for Video Deblurring,” BMVC 2021 [paper] [slides]
- Seungjun Nah, Sanghyun Son, Suyoung Lee, Radu Timofte, and Kyoung Mu Lee, “NTIRE 2021 Challenge on Image Deblurring,” CVPRW 2021 [arXiv] [paper] [slides]
- Sanghyun Son, Jaerin Lee, Seungjun Nah, Radu Timofte and Kyoung Mu Lee et al., “AIM 2020 Challenge on Video Temporal Super-Resolution,” ECCVW 2020 [paper] [arXiv] [slides]
- Seungjun Nah, Sanghyun Son, Radu Timofte and Kyoung Mu Lee et al., “NTIRE 2020 Challenge on Image and Video Deblurring,” CVPRW 2020 [paper] [arXiv] [slides] [video]
- Seungjun Nah, Sanghyun Son, Radu Timofte and Kyoung Mu Lee et al., “AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results,” ICCVW 2019 [paper] [arXiv] [slides]
- Seungjun Nah, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Radu Timofte and Kyoung Mu Lee, “NTIRE 2019 Challenge on Video Deblurring and Super-Resolution: Dataset and Study,” CVPRW 2019 [paper] [slides]
- Seungjun Nah, Sanghyun Son, and Kyoung Mu Lee, “Recurrent Neural Networks with Intra-Frame Iterations for Video Deblurring,” CVPR 2019 [paper] [slides] [poster]
- Sanghyun Son, Seungjun Nah, and Kyoung Mu Lee, “Clustering Convolutional Kernels to Compress Deep Neural Networks,” ECCV 2018 [paper] [github]
- Tae Hyun Kim, Seungjun Nah, and Kyoung Mu Lee, “Dynamic Video Deblurring using a Locally Adaptive Linear Blur Model,” PAMI 2018 [paper]
- Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee, “Enhanced Deep Residual Networks for Single Image Super-Resolution,” CVPRW 2017 (NTIRE 2017 challenge winners, workshop best paper) [paper] [github] [slides]
- Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee, “Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring,” CVPR 2017 (spotlight presentation) [paper] [arXiv] [github] [slides] [poster] [video]