wyfeng1020

wyfeng1020's Stars

• WangLibo1995/GeoSeg

  UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image and UAV image segmentation.

  Language:Python854129

• ekzhang/semantic-segmentation

  PyTorch training code for FastSeg: https://github.com/ekzhang/fastseg

  Language:Python195

• satellite-image-deep-learning/techniques

  Techniques for deep learning with satellite & aerial imagery

  9.2k1.6k

• Seyed-Ali-Ahmadi/Awesome_Satellite_Benchmark_Datasets

  Supplementary material for our paper "THERE IS NO DATA LIKE MORE DATA" is provided.

  Language:Jupyter Notebook34628

• open-mmlab/mmrotate

  OpenMMLab Rotated Object Detection Toolbox and Benchmark

  Language:Python2k574

• xmu-xiaoma666/External-Attention-pytorch

  🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

  Language:Python11.8k2k

• jbwang1997/OBBDetection

  OBBDetection is an oriented object detection library, which is based on MMdetection.

  Language:Python559118

• amusi/ICCV2023-Papers-with-Code

  ICCV 2023 论文和开源项目合集

  2.5k249

• liqiokkk/FCtL

  [ICCV 2021] "From Contexts to Locality: Ultra-high Resolution Image Segmentation via Locality-aware Contextual Correlation" by Qi Li, Weixiang Yang, Wenxi Liu, Yuanlong Yu, Shengfeng He

  Language:Python5414

• HRNet/HRNet-Semantic-Segmentation

  The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

  Language:Python3.2k689

• SimonVandenhende/Multi-Task-Learning-PyTorch

  PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020).

  Language:Python801111

• SimonVandenhende/Awesome-Multi-Task-Learning

  A list of multi-task learning papers and projects.

  37051

• jiupinjia/SkyAR

  Official Pytorch implementation of the preprint paper "Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos", in arXiv:2010.11800.

  Language:Python2k246

• mrgloom/awesome-semantic-segmentation

  :metal: awesome-semantic-segmentation

  10.6k2.5k

• CheckBoxStudio/BUAAThesis

  北航研究生学位论文模板（Word+LaTeX）.

  Language:TeX582111

• BHOSC/BUAAthesis

  北航毕设论文LaTeX模板

  Language:TeX1.1k292

• open-mmlab/mmsegmentation

  OpenMMLab Semantic Segmentation Toolbox and Benchmark.

  Language:Python8.8k2.7k

• shadowsocks/shadowsocks

  Language:Python33.6k18.5k

• amusi/AI-Job-Recommend

  国内公司人工智能方向（含机器学习、深度学习、计算机视觉和自然语言处理）岗位的招聘信息（含全职、实习和校招）

  76285

• jacquelinelala/GFN

  Gated Fusion Network for Joint Image Deblurring and Super-Resolution(BMVC 2018 Oral)

  Language:Python14239

• LikeLy-Journey/SegmenTron

  Support PointRend, Fast_SCNN, HRNet, Deeplabv3_plus(xception, resnet, mobilenet), ContextNet, FPENet, DABNet, EdaNet, ENet, Espnetv2, RefineNet, UNet, DANet, HRNet, DFANet, HardNet, LedNet, OCNet, EncNet, DuNet, CGNet, CCNet, BiSeNet, PSPNet, ICNet, FCN, deeplab)

  Language:Python709163

• YvanYin/VNL_Monocular_Depth_Prediction

  Monocular Depth Prediction

  Language:Python46779

• ankurhanda/sunrgbd-meta-data

  train test labels for sunrgbd

  Language:Matlab17431

• dontLoveBugs/DORN_pytorch

  PyTorch implementation of Deep Ordinal Regression Network for Monocular Depth Estimation

  Language:Python29866

• valeoai/DADA

  Depth-aware Domain Adaptation in Semantic Segmentation

  Language:Python11518

• lelimite4444/BridgeDepthFlow

  Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence, CVPR 2019

  Language:Python12220

• manideep2510/eye-in-the-sky

  Satellite Image Classification using semantic segmentation methods in deep learning

  Language:Python30785

• nianticlabs/monodepth2

  [ICCV 2019] Monocular depth estimation from a single image

  Language:Jupyter Notebook4.3k977

• nshaud/DeepNetsForEO

  Deep networks for Earth Observation

  Language:Jupyter Notebook477169

• jhoffman/cycada_release

  Code to accompany ICML 2018 paper

  Language:Python566127