This is the official repository for our recent work: PIDNet
A pytorch-based real-time segmentation model for autonomous driving
翻译 - 基于pytorch的自动驾驶实时分割模型
#计算机科学#Experiments with UNET/FPN models and cityscapes/kitti datasets [Pytorch]
Cityscapes to CoCo Format Conversion Tool for Mask-RCNN and Detectron
A Pytorch implementation of CASENet for the Cityscapes Dataset
Official Detectron2 implementation of DA-RetinaNet of our Image and Vision Computing 2021 work 'An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites'
Detectron2 implementation of DA-Faster R-CNN, Domain Adaptive Faster R-CNN for Object Detection in the Wild
Repository for "Stochastic Segmentation with Conditional Categorical Diffusion Models" (ICCV 2023)
【X世纪星际终端】A Wechat Social and AR Game: 基于微信聊天，结合增强现实技术AR+LBS（基于图像位置）的轻社交星际漂流瓶游戏。向外太空发送漂流信息，看看AI预测的外星人是长什么样的，寻找身边的外星人,逗逗外星生物，看看外星植物及外星建筑。Send the message to the outer space, find the aliens in the earth...
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper "Calibrated Adversarial Refinement for Stochastic Semantic Segmentation"
[ICIP 2019] : Official PyTorch implementation of the paper "What's There in The Dark" accepted in IEEE International Conference in Image Processing 2019 (ICIP19) , Taipei, Taiwan.
Implementation of the Instance Stixel pipeline. Paper:
TensorFlow implementation of a comprehensive comparison of various SSL (Semi-Supervised Learning) approaches in image segmentation, featuring our novel Inconsistency Masks (IM) method.
#计算机科学#CABiNet: Efficient Context Aggregation Network for Low-Latency Semantic Segmentation (ICRA2021)
PyTorch implementation for Semantic Segmentation on Cityscapes dataset using R2UNET and its modified version.
Collection of scripts for preparation of datasets for semantic segmentation of UAV images
#计算机科学#DSANet: Dilated Spatial Attention for Real-time Semantic Segmentation in Urban Street Scenes
#计算机科学#GPU-accelerated Semantic Image Segmentation with PyTorch
#计算机科学#Python program to visualize Deeplab (trained on Cityscapes dataset) results.
The official code open source version of BFDA - based on YOLOv5