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11/02/2022
eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers
Large-scale diffusion-based generative models have led to breakthroughs ...
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07/21/2022
CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution
Despite breakthrough advances in image super-resolution (SR) with convol...
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04/26/2022
Attentive Fine-Grained Structured Sparsity for Image Restoration
Image restoration tasks have witnessed great performance improvement in ...
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03/30/2022
Pay Attention to Hidden States for Video Deblurring: Ping-Pong Recurrent Neural Networks and Selective Non-Local Attention
Video deblurring models exploit information in the neighboring frames to...
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03/12/2022
Recurrence-in-Recurrence Networks for Video Deblurring
State-of-the-art video deblurring methods often adopt recurrent neural n...
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04/30/2021
NTIRE 2021 Challenge on Image Deblurring
Motion blur is a common photography artifact in dynamic environments tha...
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04/30/2021
NTIRE 2021 Challenge on Video Super-Resolution
Super-Resolution (SR) is a fundamental computer vision task that aims to...
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04/26/2021
Clean Images are Hard to Reblur: A New Clue for Deblurring
The goal of dynamic scene deblurring is to remove the motion blur presen...
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09/28/2020
AIM 2020 Challenge on Video Temporal Super-Resolution
Videos in the real-world contain various dynamics and motions that may l...
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05/04/2020
NTIRE 2020 Challenge on Image and Video Deblurring
Motion blur is one of the most common degradation artifacts in dynamic s...
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05/04/2020
AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
Videos contain various types and strengths of motions that may look unna...
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07/10/2017
Enhanced Deep Residual Networks for Single Image Super-Resolution
Recent research on super-resolution has progressed with the development ...
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12/07/2016
Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring
Non-uniform blind deblurring for general dynamic scenes is a challenging...
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03/14/2016
