computational-photography
There are 106 repositories under computational-photography topic.
eszdman/PhotonCamera
Android Camera that uses Enhanced image processing
HuiZeng/Image-Adaptive-3DLUT
Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
yuanming-hu/exposure
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.
texturedesign/texturize
🤖🖌️ Generate photo-realistic textures based on source images or (soon) PBR materials. Remix, remake, mashup! Useful if you want to create variations on a theme or elaborate on an existing texture.
advimman/HiDT
Official repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)
mahmoudnafifi/Deep_White_Balance
Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
mahmoudnafifi/Exposure_Correction
Project page of the paper "Learning Multi-Scale Photo Exposure Correction" (CVPR 2021).
mv-lab/AISP
AI Image SIgnal Processing and Computational Photography - Bokeh Rendering , Reversed ISP Challenge, Model-Based Image Signal Processors via Learnable Dictionaries. Official repo for NTIRE and AIM Challenges
mahmoudnafifi/WB_sRGB
White balance camera-rendered sRGB images (CVPR 2019) [Matlab & Python]
sjmoran/deeplpf-image-enhancement
Code for CVPR 2020 paper "Deep Local Parametric Filters for Image Enhancement"
sjmoran/curl-image-enhancement
Code for the ICPR 2020 paper: "CURL: Neural Curve Layers for Image Enhancement"
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.
elliottwu/DeepHDR
This is the implementation for Deep High Dynamic Range Imaging with Large Foreground Motions (ECCV'18)
wasidennis/DeepHarmonization
Demo code of the paper: "Deep Image Harmonization", Y.-H. Tsai, X. Shen, Z. Lin, K. Sunkavalli, X. Lu and M.-H. Yang, CVPR 2017
Tengfei-Wang/DCSR
[ICCV 2021 (Oral Presentation)] Dual-Camera Super-Resolution with Aligned Attention Modules (RefSR)
visionxiang/awesome-computational-photography
A curated list of awesome resources for topics related to computational photography via deep learning, which mainly focuses on image alignment and stitching.
Jamy-L/Handheld-Multi-Frame-Super-Resolution
Handheld Multi-image Super-resolution [Wronski et al., SIGGRAPH19]. Non-official GPU-supported Python implementation.
cgtuebingen/learning-blind-motion-deblurring
Multiframe Image Deconvolution (ICCV17)
mahmoudnafifi/C5
Reference code for the paper "Cross-Camera Convolutional Color Constancy" (ICCV 2021)
Rachine/ExposureFusion
Exposure Fusion Technique
cuiziteng/Aleth-NeRF
🌕 [AAAI 2024] Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption (Low-light enhance / Exposure correction + NeRF)
mahmoudnafifi/CIE_XYZ_NET
PyTorch & Matlab code for the paper: CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks (TPAMI 2021).
linusmossberg/light-field-renderer
Interactive light field renderer using dynamically reparameterized light fields.
kepengxu/RealCamNet
ACMMM'24 An End-to-End Real-World Camera Imaging Pipeline
cuiziteng/ECCV_RAW_Adapter
📷 [ECCV 2024] RAW-Adapter: Adapting Pre-trained Visual Model to Camera RAW Images
yzhq97/distortion-free-wide-angle.pytorch
Corrects perspective aberrations in wide-angle portraits. Implementation of the paper "Distortion-Free Wide-Angle Portraits on Camera Phones". Course project for 15-663 Computational Photography.
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.
srijanparmeshwar/monodepth360
Master's project implementing depth estimation for spherical images using unsupervised learning with CNNs.
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.
mauckc/colorize-video
colorize video using publicly available neural-networks
audreycui/relighting
Local Relighting of Real Scenes
jqtangust/FilmRemoval
[CVPR 2024] Official Implementation of Learning to Remove Wrinkled Transparent Film with Polarized Prior
yunchenlo/Font2Font
An enhanced zi2zi project with word-oriented data augmentation, feature combination, and transfer learning.
zhangmozhe/microshift_compression
Microshift Compression: An Efficient Image Compression Algorithm for Hardware
chetansastry/dolly-zoom
Dolly zoom without a zoom lens
nrupatunga/Fast-Image-Filters
This is PyTorch-lightning implementation of "Fast Image Processing with Fully-Convolutional Networks" (https://arxiv.org/abs/1709.00643)