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Algorithm Details

New: WildDash 2 with 4256 public frames, new labels & panoptic GT!  
See also: RailSem19 dataset for rail scene understanding.

Challenge

WD2 Panoptic

Acronym

seamseg_mvd_ps

Method title

Baseline Panoptic submission Mapillary Vistas

Method description

Seamless Scene Segmentation Panoptic Segmentation trained with altered MVD to include new WildDash 2 labels. Trained from a ResNet50 pretrained on ImageNet as a WildDash 2 baseline by Oliver Zendel/AIT

Training data

Mapillary Vistas dataset with added van/pickup truck relabeling

Parameter description

300 epochs; max. image size FullHD, batch size 2

Programming language

python/pytorch

Runtime environment

Lambda Labs Hyperblade Titan RTX

Additional data

Source code

Publication

Title

Seamless Scene Segmentation

Authors

Porzi, Lorenzo and Rota Bulò, Samuel and Colovic, Aleksander and Kontschieder, Peter

Conference

CVPR 2019

BibTex

@InProceedings{Porzi_2019_CVPR,
author = {Porzi, Lorenzo and Rota Bul\`o, Samuel and Colovic, Aleksander and Kontschieder, Peter},
title = {Seamless Scene Segmentation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}