{"url":"/dataset/deliver","name":"DELIVER","full_name":null,"description_markdown":"**DELIVER** is an arbitrary-modal segmentation benchmark, covering Depth, LiDAR, multiple Views, Events, and RGB. Aside from this, the dataset is also used in four severe weather conditions as well as five sensor failure cases to exploit modal complementarity and resolve partial outages. It is designed for the tasks of arbitrary-modal semantic segmentation.\r\n\r\nSource: [Delivering Arbitrary-Modal Semantic Segmentation](https://arxiv.org/pdf/2303.01480v1.pdf)\r\n\r\nImage Source: [https://arxiv.org/pdf/2303.01480v1.pdf](https://arxiv.org/pdf/2303.01480v1.pdf)","description_withheld":null,"homepage":"https://jamycheung.github.io/DELIVER.html","introduced_date":"2023-03-02","introduced_date_note":null,"introduced_by":{"paper":"/paper/delivering-arbitrary-modal-semantic","title":"Delivering Arbitrary-Modal Semantic Segmentation","first_author":"Jiaming Zhang","url":null},"license":{"name":"Apache-2.0 license","url":"https://github.com/jamycheung/DELIVER/blob/main/LICENSE"},"modalities":[{"name":"LiDAR","url":"/datasets/modality/lidar"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["DELIVER","DeLiVER ","DeLiVER test"],"data_loaders":[],"num_papers_in_archive":19,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/semantic-segmentation-on-deliver","task":"Semantic Segmentation","dataset_variant":"DeLiVER","rows":26,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"CAFuser-CAA","paper":"/paper/condition-aware-multimodal-fusion-for-robust","metrics":{"mIoU":"68.6"},"code_links":[{"title":"timbroed/cafuser","url":"https://github.com/timbroed/cafuser"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/semantic-segmentation-on-deliver-1","task":"Semantic Segmentation","dataset_variant":"DELIVER","rows":9,"metrics":["mIoU","test mIoU"],"first_row_in_archive_order":{"model":"CAFuser","paper":"/paper/condition-aware-multimodal-fusion-for-robust","metrics":{"mIoU":"67.8","test mIoU":"55.6"},"code_links":[{"title":"timbroed/cafuser","url":"https://github.com/timbroed/cafuser"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/semantic-segmentation-on-deliver-test","task":"Semantic Segmentation","dataset_variant":"DeLiVER test","rows":1,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"CAFuser","paper":"/paper/condition-aware-multimodal-fusion-for-robust","metrics":{"mIoU":"55.6"},"code_links":[{"title":"timbroed/cafuser","url":"https://github.com/timbroed/cafuser"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/memorysam-memorize-modalities-and-semantics","title":"MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation","date":"2025-03-09","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/condition-aware-multimodal-fusion-for-robust","title":"CAFuser: Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes","date":"2024-10-14","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/2408-01343","title":"StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation","date":"2024-08-02","rows_on_this_dataset":6,"code_links":1,"syntology":null},{"paper":"/paper/geminifusion-efficient-pixel-wise-multimodal","title":"GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer","date":"2024-06-03","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":7,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/delivering-arbitrary-modal-semantic","title":"Delivering Arbitrary-Modal Semantic Segmentation","date":"2023-03-02","rows_on_this_dataset":7,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":6,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/hrfuser-a-multi-resolution-sensor-fusion","title":"HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection","date":"2022-06-30","rows_on_this_dataset":7,"code_links":1,"syntology":null},{"paper":"/paper/multimodal-token-fusion-for-vision","title":"Multimodal Token Fusion for Vision Transformers","date":"2022-04-19","rows_on_this_dataset":3,"code_links":11,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":1,"samples_unverified":2,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/cmx-cross-modal-fusion-for-rgb-x-semantic","title":"CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers","date":"2022-03-09","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/segformer-simple-and-efficient-design-for","title":"SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers","date":"2021-05-31","rows_on_this_dataset":1,"code_links":28,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":86,"samples_ran":48,"samples_unverified":38,"pointer_only_for_licence":15,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":109,"samples_ran":65,"samples_unverified":44,"pointer_only_for_licence":16,"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."}