Seungjun Nah
Senior Research Scientist
NVIDIA
Publications | Datasets | CV
Publications (Selected)
- NVIDIA: Yuval Atzmon, Maciej Bala, Yogesh Balaji, Tiffany Cai, Yin Cui, Jiaojiao Fan, Yunhao Ge, Siddharth Gururani, Jacob Huffman, Ronald Isaac, Pooya Jannaty, Tero Karras, Grace Lam, J. P. Lewis, Aaron Licata, Yen-Chen Lin, Ming-Yu Liu, Qianli Ma, Arun Mallya, Ashlee Martino-Tarr, Doug Mendez, Seungjun Nah, Chris Pruett, Fitsum Reda, Jiaming Song, Ting-Chun Wang, Fangyin Wei, Xiaohui Zeng, Yu Zeng, Qinsheng Zhang, “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]
- 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]