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Controllable Image Enhancement



Heewon Kim , Kyoung Mu Lee


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Attentive Fine-Grained Structured Sparsity for Image Restoration



Junghun Oh , Heewon Kim , Seungjun Nah , Cheeun Hong , Jonghyun Choi , Kyoung Mu Lee


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Pay Attention to Hidden States for Video Deblurring: Ping-Pong Recurrent Neural Networks and Selective Non-Local Attention



JoonKyu Park , Seungjun Nah , Kyoung Mu Lee

* also attached the supplementary material 

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CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image



Reyhaneh Neshatavar , Mohsen Yavartanoo , Sanghyun Son , Kyoung Mu Lee

* Published at CVPR 2022 

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HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network



JoonKyu Park , Yeonguk Oh , Gyeongsik Moon , Hongsuk Choi , Kyoung Mu Lee

* Computer Vision and Pattern Recognition (CVPR), 2022 
* also attached the supplementary material 

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AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Network



Wooseok Lee , Sanghyun Son , Kyoung Mu Lee

* Accepted to CVPR2022 

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Recurrence-in-Recurrence Networks for Video Deblurring



Joonkyu Park , Seungjun Nah , Kyoung Mu Lee

* The British Machine Vision Conference (BMVC) 2021 
* accepted paper in BMVC 2021 

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C2N: Practical Generative Noise Modeling for Real-World Denoising



Geonwoon Jang , Wooseok Lee , Sanghyun Son , Kyoung Mu Lee

* Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 2350-2359 

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Batch Normalization Tells You Which Filter is Important



Junghun Oh , Heewon Kim , Sungyong Baik , Cheeun Hong , Kyoung Mu Lee


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Generative Residual Attention Network for Disease Detection



Euyoung Kim , Soochahn Lee , Kyoung Mu Lee

* The paper is about Pneumonia detection using Generative Modeling. It proposes a novel approach to construct pseudo-pair images and a GAN to generate radio-realistic Chest Xray images. Then, the paper propose to leverage the differences between the input and the generated Xray images as an additional attention-map to boost the performance in Pneumonia detection 

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