Search Results for author: Jeongmin Lee

Found 4 papers, 3 papers with code

N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution

2 code implementations CVPR 2023 Haram Choi, Jeongmin Lee, Jihoon Yang

Using the N-Gram context, we propose NGswin, an efficient SR network with SCDP bottleneck taking multi-scale outputs of the hierarchical encoder.

Image Super-Resolution

XYDeblur: Divide and Conquer for Single Image Deblurring

1 code implementation CVPR 2022 Seo-won Ji, Jeongmin Lee, Seung-Wook Kim, Jun-Pyo Hong, Seung-Jin Baek, Seung-Won Jung, Sung-Jea Ko

Many convolutional neural networks (CNNs) for single image deblurring employ a U-Net structure to estimate latent sharp images.

Deblurring Decoder +2

Event-guided Deblurring of Unknown Exposure Time Videos

no code implementations13 Dec 2021 Taewoo Kim, Jeongmin Lee, Lin Wang, Kuk-Jin Yoon

To this end, we first derive a new formulation for event-guided motion deblurring by considering the exposure and readout time in the video frame acquisition process.

Deblurring

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