{"url":"/dataset/mvx","name":"MVX","full_name":"Multimodal V2X","description_markdown":"MVX incorporates realistic physical world simulation with a differentiable accurate ray tracing wireless simulation that includes multi-agent and multimodal datasets for AI-driven digital twin applications in vehicular communication systems.","description_withheld":null,"homepage":"https://ghazigh.github.io/MVX/","introduced_date":"2024-08-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/mvx-vit-multimodal-collaborative-perception-1","title":"MVX-ViT: Multimodal Collaborative Perception for 6G V2X Network Management Decisions Using Vision Transformer.","first_author":"Ghazi Gharsallah","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Tabular","url":"/datasets/modality/tabular"},{"name":"LiDAR","url":"/datasets/modality/lidar"}],"tasks":[{"name":"3D Object Detection","url":"/task/3d-object-detection","datasets_with_task":"/datasets/task/3d-object-detection"},{"name":"Autonomous Vehicles","url":"/task/autonomous-vehicles","datasets_with_task":"/datasets/task/autonomous-vehicles"},{"name":"Intelligent Communication","url":"/task/intelligent-communication","datasets_with_task":"/datasets/task/intelligent-communication"},{"name":"Semantic Communication","url":"/task/semantic-communication","datasets_with_task":"/datasets/task/semantic-communication"},{"name":"Beam Prediction","url":"/task/beam-prediction","datasets_with_task":"/datasets/task/beam-prediction"},{"name":"Optimize the trajectory of UAV which plays a BS in communication system","url":"/task/optimize-the-trajectory-of-uav-which-plays-a","datasets_with_task":"/datasets/task/optimize-the-trajectory-of-uav-which-plays-a"}],"languages":[],"variants":["MVX"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/beam-prediction-on-mvx","task":"Beam Prediction","dataset_variant":"MVX","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"MVX-ViT","paper":"/paper/mvx-vit-multimodal-collaborative-perception-1","metrics":{"Accuracy":"88.2"},"code_links":[{"title":"ghazigh/MVX","url":"https://github.com/ghazigh/MVX"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/mvx-vit-multimodal-collaborative-perception-1","title":"MVX-ViT: Multimodal Collaborative Perception for 6G V2X Network Management Decisions Using Vision Transformer.","date":"2024-08-30","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}