city292
remote sensing, deep learning, earthquake, building damage assessment
Beijing Normal University @bnuBeijing
Pinned Repositories
3dmatch-toolbox
3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.
Awesome-NAS
A curated list of neural architecture search (NAS) resources.
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
awesome-semantic-segmentation-pytorch
Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
BasicSR
Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
BDL
BIPNet
[CVPR 2022--Oral, Best paper Finalist] Burst Image Restoration and Enhancement. SOTA for Burst Super-resolution, Low-light Burst Image Enhancement, Burst Image De-noising
build_assessment
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
keras_frcnn
Keras Implementation of faster-rcnn
city292's Repositories
city292/BasicSR
Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
city292/BDL
city292/BIPNet
[CVPR 2022--Oral, Best paper Finalist] Burst Image Restoration and Enhancement. SOTA for Burst Super-resolution, Low-light Burst Image Enhancement, Burst Image De-noising
city292/camodocal
city292/cycleGAN-PyTorch
A clean and lucid implementation of cycleGAN using PyTorch
city292/DeepLabV3Plus-Pytorch
DeepLabv3, DeepLabv3+ and pretrained weights on VOC & Cityscapes
city292/DeepRFT
The code for 'Intriguing Findings of Frequency Selection for Image Deblurring' and 'Deep Residual Fourier Transformation for Single Image Deblurring'
city292/IGEV
[CVPR 2023] Iterative Geometry Encoding Volume for Stereo Matching and Multi-View Stereo
city292/Image-Super-Resolution-via-Iterative-Refinement
Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch
city292/mean-teacher
A state-of-the-art semi-supervised method for image recognition
city292/MVision
机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶
city292/NeuralSBS
Official implementation of the NeuralSBS paper
city292/notes
my notes
city292/PVT
city292/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
city292/Real-ESRGAN
Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
city292/Restormer
[CVPR 2022--Oral] Restormer: Efficient Transformer for High-Resolution Image Restoration. SOTA for motion deblurring, image deraining, denoising (Gaussian/real data), and defocus deblurring.
city292/SCGLANet
city292/seg_net
city292/segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
city292/SETR
[CVPR 2021] Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
city292/spinningup
An educational resource to help anyone learn deep reinforcement learning.
city292/StableSR
Exploiting Diffusion Prior for Real-World Image Super-Resolution
city292/stereo_rectify
city292/Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
city292/T2T-ViT
city292/tc_2021
2021全国数字生态创新大赛
city292/TENet
[ICCP'22] Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline
city292/USSS_ICCV19
Code for Universal Semi-Supervised Semantic Segmentation models paper accepted in ICCV 2019
city292/ViT-pytorch
Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)