WeikaiTan's starred repositories
awesome-satellite-imagery-datasets
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
pytorch-image-models
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more
External-Attention-pytorch
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
KPConv-PyTorch
Kernel Point Convolution implemented in PyTorch
Pointnet2_PyTorch
PyTorch implementation of Pointnet2/Pointnet++
Swin-Transformer
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
PlotNeuralNet
Latex code for making neural networks diagrams
Open3D-PointNet2-Semantic3D
Semantic3D segmentation with Open3D and PointNet++
AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2022
eat_pytorch_in_20_days
Pytorch🍊🍉 is delicious, just eat it! 😋😋
eat_tensorflow2_in_30_days
Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋
SensatUrban
🔥Urban-scale point cloud dataset (CVPR 2021 & IJCV 2022)
Sparse-Depth-Completion
Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [MVA 2019]
self-supervised-depth-completion
ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"
SciencePlots
Matplotlib styles for scientific plotting
livox_high_precision_mapping
High precision mapping with livox and apx-15
ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
lidar_super_resolution
Simulation-based Lidar Super-resolution for Ground Vehicles
interpretable-ml-book
Book about interpretable machine learning