dual-pixel

There are 0 repository under dual-pixel topic.

• Abdullah-Abuolaim / defocus-deblurring-dual-pixel

  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.

  defocus-blurdefocus-deblurringdual-pixeldepth-of-fieldautofocusdeep-neural-networksdeeplearningdatasetscomputational-photographydatasetdeep-learningcomputer-vision
  Language:Python 163

• Abdullah-Abuolaim / recurrent-defocus-deblurring-synth-dual-pixel

  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.

  defocus-blurdefocus-deblurringdual-pixeldepth-of-fieldautofocusdeep-neural-networksrecurrent-neural-networksdeeplearningdatasetsynthetic-datasynthetic-dataset-generationcomputational-photographydeep-learningdatasetscomputer-vision
  Language:Python 44

• Abdullah-Abuolaim / multi-task-defocus-deblurring-dual-pixel-nimat

  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.

  deep-neural-networkscomputer-visiondeep-learningdatasetdeeplearningdatasetscomputational-photographyautofocussynthetic-datadepth-of-fieldsynthetic-dataset-generationdefocus-blurdefocus-deblurringdual-pixelimage-motionnimat-effect
  Language:Python 42

• MinJunKang / DualPixelFace

  Facial Depth and Normal Estimation using Dual-Pixel Camera (ECCV 22)

  deep-learningdepth-estimationdual-pixelface-reconstructionnormal-estimation
  Language:Python 29

• feiran-l / Neural-Dual-Pixel-Simulator

  Code & Dataset release for the ICCP'23 paper: Learning to Synthesize Photorealistic Dual-pixel Images from RGBD frames

  computational-photographydual-pixelimage-processingimage-synthesis
  Language:Python 5