{"url":"/dataset/replica","name":"Replica","full_name":null,"description_markdown":"The Replica Dataset is a dataset of high quality reconstructions of a variety of indoor spaces. Each reconstruction has clean dense geometry, high resolution and high dynamic range textures, glass and mirror surface information, planar segmentation as well as semantic class and instance segmentation. \r\n\r\nSource: [The Replica Dataset: A Digital Replica of Indoor Spaces](/paper/the-replica-dataset-a-digital-replica-of)","description_withheld":null,"homepage":"https://github.com/facebookresearch/Replica-Dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/the-replica-dataset-a-digital-replica-of","title":"The Replica Dataset: A Digital Replica of Indoor Spaces","first_author":"Julian Straub","url":null},"license":{"name":"Custom","url":"https://github.com/facebookresearch/Replica-Dataset/blob/master/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Image Generation","url":"/task/image-generation","datasets_with_task":"/datasets/task/image-generation"},{"name":"Domain Adaptation","url":"/task/domain-adaptation","datasets_with_task":"/datasets/task/domain-adaptation"},{"name":"Visual Navigation","url":"/task/visual-navigation","datasets_with_task":"/datasets/task/visual-navigation"},{"name":"Scene Generation","url":"/task/scene-generation","datasets_with_task":"/datasets/task/scene-generation"},{"name":"3D Open-Vocabulary Instance Segmentation","url":"/task/3d-open-vocabulary-instance-segmentation","datasets_with_task":"/datasets/task/3d-open-vocabulary-instance-segmentation"},{"name":"Efficient Exploration","url":"/task/efficient-exploration","datasets_with_task":"/datasets/task/efficient-exploration"}],"languages":[],"variants":["Replica"],"data_loaders":[{"repo":"https://github.com/facebookresearch/Replica-Dataset","url":"https://github.com/facebookresearch/Replica-Dataset","frameworks":[]}],"num_papers_in_archive":414,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-open-vocabulary-instance-segmentation-on-1","task":"3D Open-Vocabulary Instance Segmentation","dataset_variant":"Replica","rows":7,"metrics":["mAP"],"first_row_in_archive_order":{"model":"Open-YOLO 3D","paper":"/paper/open-yolo-3d-towards-fast-and-accurate-open","metrics":{"mAP":"23.7"},"code_links":[{"title":"aminebdj/openyolo3d","url":"https://github.com/aminebdj/openyolo3d"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/semantic-segmentation-on-replica","task":"Semantic Segmentation","dataset_variant":"Replica","rows":5,"metrics":["mIoU"],"first_row_in_archive_order":{"model":"LabelMaker","paper":"/paper/labelmaker-automatic-semantic-label","metrics":{"mIoU":"42.1"},"code_links":[{"title":"cvg/labelmaker","url":"https://github.com/cvg/labelmaker"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/image-generation-on-replica","task":"Image Generation","dataset_variant":"Replica","rows":4,"metrics":["FID","FID (SwAV)"],"first_row_in_archive_order":{"model":"GAUDI","paper":"/paper/gaudi-a-neural-architect-for-immersive-3d","metrics":{"FID":"18.75","FID (SwAV)":"1.76"},"code_links":[{"title":"apple/ml-gaudi","url":"https://github.com/apple/ml-gaudi"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/scene-generation-on-replica","task":"Scene Generation","dataset_variant":"Replica","rows":3,"metrics":["FID","SwAV-FID"],"first_row_in_archive_order":{"model":"GSN","paper":"/paper/unconstrained-scene-generation-with-locally","metrics":{"FID":"41.75","SwAV-FID":"4.14"},"code_links":[{"title":"apple/ml-gsn","url":"https://github.com/apple/ml-gsn"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/open-yolo-3d-towards-fast-and-accurate-open","title":"Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation","date":"2024-06-04","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":4,"samples_unverified":7,"pointer_only_for_licence":11,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/open3dis-open-vocabulary-3d-instance","title":"Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask Guidance","date":"2023-12-17","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":8,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/labelmaker-automatic-semantic-label","title":"LABELMAKER: Automatic Semantic Label Generation from RGB-D Trajectories","date":"2023-11-20","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; 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not a correctness claim."}},{"paper":"/paper/mask3d-for-3d-semantic-instance-segmentation","title":"Mask3D: Mask Transformer for 3D Semantic Instance Segmentation","date":"2022-10-06","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":2,"samples_unverified":8,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/gaudi-a-neural-architect-for-immersive-3d","title":"GAUDI: A Neural Architect for Immersive 3D Scene Generation","date":"2022-07-27","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"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":1,"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/unconstrained-scene-generation-with-locally","title":"Unconstrained Scene Generation with Locally Conditioned Radiance Fields","date":"2021-04-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/pi-gan-periodic-implicit-generative","title":"pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis","date":"2020-12-02","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":3,"samples_unverified":1,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/graf-generative-radiance-fields-for-3d-aware","title":"GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis","date":"2020-07-05","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":3,"samples_unverified":9,"pointer_only_for_licence":0,"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":13,"samples_harvested":78,"samples_ran":43,"samples_unverified":35,"pointer_only_for_licence":15,"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."}