Datasets › V2X-SIM
V2X-SIM
V2X-Sim, short for vehicle-to-everything simulation, is the a synthetic collaborative perception dataset in autonomous driving developed by AI4CE Lab at NYU and MediaBrain Group at SJTU to facilitate collaborative perception between multiple vehicles and roadside infrastructure. Data is collected from both roadside and vehicles when they are presented near the same intersection. With information from both the roadside infrastructure and vehicles, the dataset aims to encourage research on collaborative perception tasks.
Although not collected from the real world, highly realistic traffic simulation software is used to ensure the representativeness of the dataset compared to real-world driving scenarios. To be more exact, the traffic flow of the recording files is managed by CARLA-SUMO co-simulation, and three town maps from CARLA are currently used to increase the diversity of the dataset.
Here is a tutorial showing how to load the dataset: https://ai4ce.github.io/V2X-Sim/tutorial.html
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| 3D Object Detection | V2X-SIM | QUEST mAP 23.9 | QUEST: Query Stream for Practical Cooperative Perception | leofansq/QUEST | 5 | Compare |
Papers archive 2025-07-28
5 shown of 5 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 32. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| QUEST: Query Stream for Practical Cooperative Perception | 1 | 1 | 3 Aug 2023 | not harvested |
| Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps | 1 | 1 | 26 Sep 2022 | ran 4 of 6 samples (2 unverified; 6 pointer-only for licence) |
| V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer | 1 | 1 | 20 Mar 2022 | ran 0 of 3 samples (3 unverified) |
| Learning Distilled Collaboration Graph for Multi-Agent Perception | 2 | 1 | 1 Nov 2021 | ran 4 of 6 samples (2 unverified) |
| V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction | 3 | 1 | 17 Aug 2020 | ran 2 of 2 samples (0 unverified; 2 pointer-only for licence) |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Custom
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- V2X-SIM
1 variant name, as the archive lists them.
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