Topic: defocus-deblurring Goto Github
Some thing interesting about defocus-deblurring
Some thing interesting about defocus-deblurring
defocus-deblurring,Reference github repository for the paper "Defocus Deblurring Using Dual-Pixel Data". We introduce a deep neural network (DNN) architecture that uses the dual-pixel (DP) sub-aperture views to reduce defocus blur.
User: abdullah-abuolaim
defocus-deblurring,Reference github repository for the paper "Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning". We propose a single-image deblurring network that incorporates the two sub-aperture views into a multitask framework. Specifically, we show that jointly learning to predict the two DP views from a single blurry input image improves the network’s ability to learn to deblur the image. Our experiments show this multi-task strategy achieves +1dB PSNR improvement over state-of-the-art defocus deblurring methods. In addition, our multi-task framework allows accurate DP-view synthesis (e.g., ~ 39dB PSNR) from the single input image. These high-quality DP views can be used for other DP-based applications, such as reflection removal. As part of this effort, we have captured a new dataset of 7,059 high-quality images to support our training for the DP-view synthesis task.
User: abdullah-abuolaim
defocus-deblurring,Reference github repository for the paper "Learning to Reduce Defocus Blur by Realistically Modeling Dual-Pixel Data". We propose a procedure to generate realistic DP data synthetically. Our synthesis approach mimics the optical image formation found on DP sensors and can be applied to virtual scenes rendered with standard computer software. Leveraging these realistic synthetic DP images, we introduce a new recurrent convolutional network (RCN) architecture that can improve defocus deblurring results and is suitable for use with single-frame and multi-frame data captured by DP sensors.
User: abdullah-abuolaim
defocus-deblurring,Images and video restoration in multiple-stages using MIRNETv2 model, additionally object detection on images and video through FASTER-RCNN . And complete web application in flask including responsive front-end
User: ahmednaseer01
defocus-deblurring,[ICLR 2023] Selective Frequency Network for Image Restoration
User: c-yn
defocus-deblurring,[CVPR 2019] Official TensorFlow Implementation for "Deep Defocus Map Estimation using Domain Adaptation"
User: codeslake
defocus-deblurring,[CVPR 2021] Official PyTorch Implementation for "Iterative Filter Adaptive Network for Single Image Defocus Deblurring"
User: codeslake
defocus-deblurring,[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"
User: hyeongseokson1
defocus-deblurring,[CVPR Oral 2022] PyTorch Implementation for "Learning to Deblur using Light Field Generated and Real Defocused Images"
User: lingyanruan
defocus-deblurring,Revisiting Image Deblurring with an Efficient ConvNet - An efficient CNN performs better than Transformer
User: lingyanruan
defocus-deblurring,Modeling defocus blur with linearity constraints in the latent space
User: nis-research
defocus-deblurring,Defocusによる画像ボケを利用した深度推定
User: panda5mt
defocus-deblurring,A curated list of resources for Image and Video Deblurring
User: subeeshvasu
defocus-deblurring,[TPAMI 2022] Learning Enriched Features for Fast Image Restoration and Enhancement. Results on Defocus Deblurring, Denoising, Super-resolution, and image enhancement
User: swz30
defocus-deblurring,[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
User: swz30
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