cityscapes dataset paper
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The Cityscapes Dataset for Semantic Urban Scene Understanding
Designing a large-scale dataset requires a multitude of decisions e g on the modalities of data recording data preparation and the annotation protocol Our choices were guided by the ultimate goal of enabling significant progress in the field of semantic urban scene understanding |
How many pixel-level annotations are there in a large-scale dataset?
We present a new large-scale dataset that contains a diverse set of stereo video sequences recorded in street scenes from 50 different cities, with high quality pixel-level annotations of 5 000 frames in addition to a larger set of 20 000 weakly annotated frames. The dataset is thus an order of magnitude larger than similar previous attempts.
How many cities does cityscapes cover?
As Cityscapes provides recordings from 50 differ-ent cities, it also covers a significantly larger area than pre-vious datasets that contain images from a single city only, e.g. Cambridge (CamVid), Heidelberg (DUS), and Karl-sruhe (KITTI).
Where can I find information about cityscapes dataset?
Several aspects are still up for discussion, and timely feed-back from the community would be greatly appreciated. Details on annotated classes and examples will be available at www. cityscapes-dataset.net. Moreover, we will use this web-site to collect remarks and suggestions.
2. Dataset
Designing a large-scale dataset requires a multitude of decisions, e.g. on the modalities of data recording, data preparation, and the annotation protocol. Our choices were guided by the ultimate goal of enabling significant progress in the field of semantic urban scene understanding. arxiv.org
3. Semantic Labeling
The first Cityscapes task involves predicting a per-pixel semantic labeling of the image without considering higher-level object instance or boundary information. arxiv.org
3.1. Tasks and metrics
To assess labeling performance, we rely on a standard and a novel metric. The first is the standard Jaccard Index, commonly known as the PASCAL VOC intersection-over-union metric IoU = TP [14], where TP, FP, and TP+FP+FN FN are the numbers of true positive, false positive, and false negative pixels, respectively, determined over the whole test set
4. Instance-Level Semantic Labeling
The pixel-level task, c.f. Sec. 3, does not aim to segment individual object instances. In contrast, in the instance-level semantic labeling task, we focus on simultaneously detecting objects and segmenting them. This is an exten-sion to both traditional object detection, since per-instance segments must be provided, and semantic labeling, since ea
A. Related Datasets
In Tab. 7 we provide a comparison to other related datasets in terms of the type of annotations, the meta infor-mation provided, the camera perspective, the type of scenes, and their size. The selected datasets are either of large scale or focus on street scenes. arxiv.org
D. Detailed Results
In this section, we present additional details regarding our control experiments and baselines. Specifically, we give individual class scores that complement the aggregated scores in the main paper. Moreover, we provide details on the training procedure for all baselines. Finally, we show additional qualitative results of all methods. arxiv.org
Cityscapes Dataset
Cityscapes Dataset
PIDNet-S Semantic Segmentation on Cityscapes Dataset｜2022【MY Computer Vision】
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The Cityscapes Dataset for Semantic Urban Scene Understanding
Cityscapes is comprised of a large diverse set of stereo video sequences recorded in streets from 50 different cities. 5000 of these images have high quality |
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Night-time Scene Parsing with a Large Real Dataset
24 nov. 2020 In this paper we address the night-time scene parsing (NTSP) ... Schiele |
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Amodal Cityscapes: A New Dataset its Generation
https://ieeexplore.ieee.org/iel7/9826996/9826997/09827342.pdf |
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The Mapillary Vistas Dataset for Semantic Understanding of Street
Our dataset is 5× larger than the total amount of fine annotations for. Cityscapes and contains images from all around the world captured at various conditions |
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Universal Semantic Segmentation for Fisheye Urban Driving Images
24 août 2020 CityScapes dataset [3] is a well-known dataset in the field of ... This paper proposes a general virtual fisheye data augmen- tation method ... |
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The Cityscapes Dataset
In this paper we present ongoing work on a new large-scale dataset for (1) assessing the performance of vision algorithms for differ- ent tasks of semantic |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
To address this we introduce Cityscapes |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
Specifically we give individual class scores that complement the aggregated scores in the main paper. Moreover |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
7 avr. 2016 Exemplary output of our baseline experiments for the pixel-level semantic labeling task see the main paper for details. The image is part ... |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
To address this we introduce Cityscapes |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
To address this we introduce Cityscapes |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
To address this we introduce Cityscapes |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
To address this we introduce Cityscapes |
|
The Cityscapes Dataset
In this paper we present ongoing work on a new large-scale dataset for (1) assessing the performance of vision al- gorithms for different tasks of semantic |
|
The Cityscapes Dataset for Semantic Urban Scene Understanding
7 Apr 2016 We compare Cityscapes to other datasets in terms of (i) ... See the main paper for details on the listed methods. |
| The Cityscapes Dataset for Semantic Urban Scene Understanding |
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Learning Texture Invariant Representation for Domain Adaptation of
30 Mar 2020 paper considering the fundamental difference between the ... to make ground truth label for the Cityscape [5] dataset. |
| Supplementary Material for Prior-based Domain Adaptive Object |
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ResSCNN: A semantic segmentation method for fast processing of
In this paper we combine the large-scale input Fast-SCNN with the residual Cityscapes dataset has a huge amount of data and extremely fine labelling ... |
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IDD: A Dataset for Exploring Problems of Autonomous Navigation in
26 Nov 2018 such as Cityscapes to account for new classes. It also re- ... In this paper |
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Paper - Cityscapes Dataset
The Cityscapes Dataset Marius Cordts1 In this paper, we present ongoing work on a new more challenging datasets have been created to push forward the |
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The Cityscapes Dataset for Semantic Urban Scene Understanding
Specifically, we give individual class scores that complement the aggregated scores in the main paper Moreover, we provide details on the training procedure for |
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A Review of Neural Network based Semantic Segmentation - CORE
This paper tackles the challenge of scene understanding in context of automated driving To react result of the network trained on the Cityscapes Dataset |
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Semantic Segmentation Datasets for Resource Constrained Training
introduced Cityscapes [5] and India Driving Dataset [16](IDD) which provide finely annotated More recent papers on architecture search have shifted to |
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MSeg: A Composite Dataset for Multi-domain - Vladlen Koltun
Hundreds of papers are published every year that re- port ever-higher accuracy on semantic segmentation bench- marks such as Cityscapes [7], Mapillary [25], |
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Pyramid Scene Parsing Network - Jiaya Jia
In this paper, we exploit the which are key to our decent performance in this paper, and cityscapes dataset for semantic urban scene understanding |
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PanDA: Panoptic Data Augmentation
datasets, such as the Cityscapes [5], Microsoft COCO [17], ADE20K [29], and In this paper, insead of developing new models, we focus on the data augmen- |
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A Large-Scale Sidewalk Dataset for Guiding Impaired People
Abstract—In this paper, we introduce a new large-scale sidewalk Cityscapes [2 ]) nenson, U Franke, S Roth, and B Schiele, “The Cityscapes Dataset |
![PDF] Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle](https://www.cityscapes-dataset.com/wordpress/wp-content/uploads/2015/07/lindau00.png "PDF] Cityscapes 3D: Dataset and Benchmark for 9 DoF Vehicle")
