Data to 7 Oct 2026

Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing

arXiv 1810.08705 ↗First posted 19 Oct 2018cs.CVcited by 105

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Abstract (arXiv)

We introduce Synscapes -- a synthetic dataset for street scene parsing created using photorealistic rendering techniques, and show state-of-the-art results for training and validation as well as new types of analysis. We study the behavior of networks trained on real data when performing inference on synthetic data: a key factor in determining the equivalence of simulation environments. We also compare the behavior of networks trained on synthetic data and evaluated on real-world data. Additionally, by analyzing pre-trained, existing segmentation and detection models, we illustrate how uncorrelated images along with a detailed set of annotations open up new avenues for analysis of computer vision systems, providing fine-grain information about how a model's performance changes according to factors such as distance, occlusion and relative object orientation.

Key facts. Cited by 105 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Oct 2018.

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Citing papers per year: 2021: 17; 2022: 19; 2023: 17; 2024: 16; 2025: 19; 2026: 17.

105 papers.

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2025Continuous 3D Perception Model with Persistent Statecited by 527
2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 395
2025MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Detailscited by 250
2023Infinite Photorealistic Worlds using Procedural Generationcited by 142
2021Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weathercited by 95
2022High-Quality Entity Segmentationcited by 93
2023Language Conditioned Traffic Generationcited by 86
2024A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlookcited by 65
2022Balancing Discriminability and Transferability for Source-Free Domain Adaptationcited by 58
2023Synthetic Datasets for Autonomous Driving: A Surveycited by 48
2021Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentationcited by 44
2023All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenescited by 40

38 more

2023Template Free Reconstruction of Human-object Interaction with Procedural Interaction Generationcited by 37
2024A survey of synthetic data augmentation methods in computer visioncited by 34
2021Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentationcited by 33
2022Deliberated Domain Bridging for Domain Adaptive Semantic Segmentationcited by 31
2023Semantic Image Segmentation: Two Decades of Researchcited by 26
2021Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentationcited by 24
2021Semi-supervised Multi-task Learning for Semantics and Depthcited by 22
2021Unsupervised Domain Adaptation for Semantic Image Segmentation: a Comprehensive Surveycited by 19
2023SyntheWorld: A Large-Scale Synthetic Dataset for Land Cover Mapping and Building Change Detectioncited by 19
2022PSP-HDRI+: A Synthetic Dataset Generator for Pre-Training of Human-Centric Computer Vision Modelscited by 15
2023CSL: Class-Agnostic Structure-Constrained Learning for Segmentation Including the Unseencited by 15
2022Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detectioncited by 14
2023Multi-Source Domain Adaptation for Object Detection with Prototype-based Mean-teachercited by 13
2024High-Quality Entity Segmentation and Groundingcited by 13
2024LAKE-RED: Camouflaged Images Generation by Latent Background Knowledge Retrieval-Augmented Diffusioncited by 12
2021PeopleSansPeople: A Synthetic Data Generator for Human-Centric Computer Visioncited by 11
2022Ad-datasets: a meta-collection of data sets for autonomous drivingcited by 11
2022Urban Scene Semantic Segmentation with Low-Cost Coarse Annotationcited by 11
2026MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sourcescited by 10
2021Personalized Image Semantic Segmentationcited by 9
2023Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweightingcited by 9
2024SynRS3D: A Synthetic Dataset for Global 3D Semantic Understanding from Monocular Remote Sensing Imagerycited by 9
2025Enhancing Autonomous Driving Safety with Collision Scenario Integrationcited by 9
2021Cross-Region Domain Adaptation for Class-level Alignmentcited by 8
2022Mind The Edge: Refining Depth Edges in Sparsely-Supervised Monocular Depth Estimationcited by 8
2024SEED4D: A Synthetic Ego--Exo Dynamic 4D Data Generator, Driving Dataset and Benchmarkcited by 8
2022Birds of A Feather Flock Together: Category-Divergence Guidance for Domain Adaptive Segmentationcited by 7
2022Co-Training for Unsupervised Domain Adaptation of Semantic Segmentation Modelscited by 7
2022Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based Approachcited by 7
2024Generating Diverse Agricultural Data for Vision-Based Farming Applicationscited by 7
2021SPCL: A New Framework for Domain Adaptive Semantic Segmentation via Semantic Prototype-based Contrastive Learningcited by 6
2021TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentationcited by 5
2023Object Detector Differences when using Synthetic and Real Training Datacited by 5
2024Synthetic Data Generation Framework, Dataset, and Efficient Deep Model for Pedestrian Intention Predictioncited by 5
2024WheelPose: Data Synthesis Techniques to Improve Pose Estimation Performance on Wheelchair Userscited by 5
2025RICO: Two Realistic Benchmarks and an In-Depth Analysis for Incremental Learning in Object Detectioncited by 5
2026PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimationcited by 5
2022Reducing the Amount of Real World Data for Object Detector Training with Synthetic Datacited by 4

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