JSTASR-DesnowNet-ECCV-2020This is the project page of our paper which has been published in ECCV 2020.
Stars: ✭ 17 (-59.52%)
Mutual labels: dehaze, dehazing
SwinIRSwinIR: Image Restoration Using Swin Transformer (official repository)
Stars: ✭ 1,260 (+2900%)
Mutual labels: super-resolution, low-level-vision
GMAN Net Haze RemovalSingle Image Dehazing with a Generic Model-Agnostic Convolutional Neural Network
Stars: ✭ 28 (-33.33%)
Mutual labels: dehaze
SR FrameworkA generic framework which implements some famouts super-resolution models
Stars: ✭ 54 (+28.57%)
Mutual labels: super-resolution
EmiyaEngine只要蘊藏著想成為真物的意志,偽物就比真物還要來得真實。
Stars: ✭ 27 (-35.71%)
Mutual labels: super-resolution
libsrcnnSuper-Resolution imaging with Convolutional Neural Network library for G++, Non-OpenCV model.
Stars: ✭ 14 (-66.67%)
Mutual labels: super-resolution
LightFieldReconstructionHigh-Dimensional Dense Residual Convolutional Neural Network for Light Field Reconstruction
Stars: ✭ 50 (+19.05%)
Mutual labels: super-resolution
Super resolution SurveyA survey of recent application of deep learning on super-resolution tasks
Stars: ✭ 32 (-23.81%)
Mutual labels: super-resolution
ECNDNetEnhanced CNN for image denoising (CAAI Transactions on Intelligence Technology, 2019)
Stars: ✭ 58 (+38.1%)
Mutual labels: low-level-vision
tf-bsrn-srOfficial implementation of block state-based recursive network (BSRN) for super-resolution in TensorFlow
Stars: ✭ 28 (-33.33%)
Mutual labels: super-resolution
EDVR KerasKeras implementation of EDVR: Video Restoration with Enhanced Deformable Convolutional Networks
Stars: ✭ 35 (-16.67%)
Mutual labels: super-resolution
TC-YoukuVSRE天池2019阿里巴巴优酷视频增强和超分辨率挑战赛自用代码,EDVR、WDSR、ESRGAN三个模型。
Stars: ✭ 41 (-2.38%)
Mutual labels: super-resolution
CF-NetOfficial repository of "Deep Coupled Feedback Network for Joint Exposure Fusion and Image Super-Resolution"
Stars: ✭ 55 (+30.95%)
Mutual labels: super-resolution
FISROfficial repository of FISR (AAAI 2020).
Stars: ✭ 72 (+71.43%)
Mutual labels: super-resolution
dehaze[Preprint] "Improved Techniques for Learning to Dehaze and Beyond: A Collective Study"
Stars: ✭ 46 (+9.52%)
Mutual labels: dehaze
CWRCode and dataset for Single Underwater Image Restoration by Contrastive Learning, IGARSS 2021, oral.
Stars: ✭ 43 (+2.38%)
Mutual labels: low-level-vision
ECBSREdge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices, ACM Multimedia 2021
Stars: ✭ 216 (+414.29%)
Mutual labels: super-resolution
PNG-UpscaleAI Super - Resolution
Stars: ✭ 116 (+176.19%)
Mutual labels: super-resolution