xianglingliwei's starred repositories
ddpm-segmentation
Label-Efficient Semantic Segmentation with Diffusion Models (ICLR'2022)
RGBD_Semantic_Segmentation_PyTorch
[ECCV 2020] PyTorch Implementation of some RGBD Semantic Segmentation models.
py-gdalogr-cookbook
A cookbook full of recipes for using the Python GDAL/OGR bindings.
DA-TransUnet
DA-TransUNet: Combining Dual Attention of Position and Channel with Transformer U-net for Medical Image Segmentation
py-gdalogr-cookbook-zh
python GDAL/OGR 中文手册
GradCAM_Automation
A GradCAM automatic script to visualize the model result
TransFusionX
Multi-Modal Fusion Network for Semantic Segmentation
multimodalperception
Supplementary material for "Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges" IEEE transactions on intelligent transportation systems: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9000872 -- arxiv: https://arxiv.org/pdf/1902.07830.pdf
LSKDiffDet
The code implementation of the remote object detection method, described in the paper
MultiModalSeg
Multi-modal semantic segmentation
BrainTumorSegmentation
A deep learning model that performs semantic segmentation of brain tumors from multi-modal MR images. Trained with data from: https://www.kaggle.com/datasets/awsaf49/brats20-dataset-training-validation
multi_modal_3d_unet
MRI's have been one of the go-to methods for diagnosis of brain tumors by radiologists. In this repository, we implement a multi-modal (T2 FLAIR, T1w, T1Gd and T2w) 3D semantic segmentation model (3D Unet) to automatically segment whole tumor, tumor core and enhancing tumor.
RS-classification-DBAF-Net
A Dual–Branch Attention fusion deep network for multiresolution remote–Sensing image classification
Project2-3D_Perception
Multi-Modal Semantic Segmentation using traditional algorithms for data-fusion