cityscapes-dataset

This is the official repository for our recent work: PIDNet

A pytorch-based real-time segmentation model for autonomous driving

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, An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites, Image and Vision Computing (IMAVIS) 2021

Detectron2 implementation of DA-Faster R-CNN, Domain Adaptive Faster R-CNN for Object Detection in the Wild, Computer Vision and Pattern Recognition (CVPR) 2018

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. Let`s see what they look like from LSGAN`s prediction. Also, Have a look at the aliens' pets and the vegetation from the outer space

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.

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

DSANet: Dilated Spatial Attention for Real-time Semantic Segmentation in Urban Street Scenes

GPU-accelerated Semantic Image Segmentation with PyTorch

Python program to visualize Deeplab (trained on Cityscapes dataset) results.

The official code open source version of BFDA - based on YOLOv5