{"url":"/dataset/pix3d","name":"Pix3D","full_name":null,"description_markdown":"The **Pix3D** dataset is a large-scale benchmark of diverse image-shape pairs with pixel-level 2D-3D alignment. Pix3D has wide applications in shape-related tasks including reconstruction, retrieval, viewpoint estimation, etc.\r\n\r\nSource: [http://pix3d.csail.mit.edu/](http://pix3d.csail.mit.edu/)\r\nImage Source: [http://pix3d.csail.mit.edu/](http://pix3d.csail.mit.edu/)","description_withheld":null,"homepage":"http://pix3d.csail.mit.edu/","introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/pix3d-dataset-and-methods-for-single-image-3d","title":"Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling","first_author":"Xingyuan Sun","url":null},"license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"Pose Estimation","url":"/task/pose-estimation","datasets_with_task":"/datasets/task/pose-estimation"},{"name":"3D Shape Reconstruction","url":"/task/3d-shape-reconstruction","datasets_with_task":"/datasets/task/3d-shape-reconstruction"},{"name":"3D Shape Modeling","url":"/task/3d-shape-modeling","datasets_with_task":"/datasets/task/3d-shape-modeling"},{"name":"3D Shape Classification","url":"/task/3d-shape-retrieval","datasets_with_task":"/datasets/task/3d-shape-retrieval"}],"languages":[],"variants":["Pix3D S2","Pix3D S1","Pix3D"],"data_loaders":[],"num_papers_in_archive":142,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/3d-shape-reconstruction-on-pix3d","task":"3D Shape Reconstruction","dataset_variant":"Pix3D","rows":5,"metrics":["CD","EMD","IoU"],"first_row_in_archive_order":{"model":"IM3D","paper":"/paper/holistic-3d-scene-understanding-from-a-single-1","metrics":{"CD":"0.0672","EMD":"N/A","IoU":"N/A"},"code_links":[{"title":"chengzhag/Implicit3DUnderstanding","url":"https://github.com/chengzhag/Implicit3DUnderstanding"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/3d-shape-retrieval-on-pix3d","task":"3D Shape Classification","dataset_variant":"Pix3D","rows":3,"metrics":["R@1","R@16","R@2","R@32","R@4","R@8"],"first_row_in_archive_order":{"model":"MarrNet extension (w/o Pose)","paper":"/paper/pix3d-dataset-and-methods-for-single-image-3d","metrics":{"R@1":"0.53","R@16":"0.85","R@2":"0.62","R@32":"0.90","R@4":"0.71","R@8":"0.78"},"code_links":[{"title":"xingyuansun/pix3d","url":"https://github.com/xingyuansun/pix3d"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/3d-shape-modeling-on-pix3d-s1","task":"3D Shape Modeling","dataset_variant":"Pix3D S1","rows":1,"metrics":["box AP","mask AP","mesh AP"],"first_row_in_archive_order":{"model":"Mesh R-CNN","paper":"/paper/mesh-r-cnn","metrics":{"box AP":"94.0","mask AP":"88.4","mesh AP":"51.1"},"code_links":[{"title":"facebookresearch/pytorch3d","url":"https://github.com/facebookresearch/pytorch3d"},{"title":"facebookresearch/meshrcnn","url":"https://github.com/facebookresearch/meshrcnn"},{"title":"huang229/auto_tooth_arrangement","url":"https://github.com/huang229/auto_tooth_arrangement"},{"title":"IMAC-projects/mesh-deformation","url":"https://github.com/IMAC-projects/mesh-deformation"},{"title":"Penguinazor/mse.wem.project","url":"https://github.com/Penguinazor/mse.wem.project"},{"title":"theycallmepeter/pytorch3d_PBR","url":"https://github.com/theycallmepeter/pytorch3d_PBR"},{"title":"xhxuciedu/3DHand","url":"https://github.com/xhxuciedu/3DHand"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/3d-shape-modeling-on-pix3d-s2","task":"3D Shape Modeling","dataset_variant":"Pix3D S2","rows":1,"metrics":["box AP","mask AP","mesh AP"],"first_row_in_archive_order":{"model":"Mesh R-CNN","paper":"/paper/mesh-r-cnn","metrics":{"box AP":"72.2","mask AP":"63.9 ","mesh AP":"28.8"},"code_links":[{"title":"facebookresearch/pytorch3d","url":"https://github.com/facebookresearch/pytorch3d"},{"title":"facebookresearch/meshrcnn","url":"https://github.com/facebookresearch/meshrcnn"},{"title":"huang229/auto_tooth_arrangement","url":"https://github.com/huang229/auto_tooth_arrangement"},{"title":"IMAC-projects/mesh-deformation","url":"https://github.com/IMAC-projects/mesh-deformation"},{"title":"Penguinazor/mse.wem.project","url":"https://github.com/Penguinazor/mse.wem.project"},{"title":"theycallmepeter/pytorch3d_PBR","url":"https://github.com/theycallmepeter/pytorch3d_PBR"},{"title":"xhxuciedu/3DHand","url":"https://github.com/xhxuciedu/3DHand"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/pose-estimation-on-pix3d","task":"Pose Estimation","dataset_variant":"Pix3D","rows":1,"metrics":["Percentage correct"],"first_row_in_archive_order":{"model":"Mid-Level based","paper":"/paper/object-pose-estimation-using-mid-level-visual","metrics":{"Percentage correct":"74.55"},"code_links":[{"title":"n-nejatishahidin/pose_from_mid-level","url":"https://github.com/n-nejatishahidin/pose_from_mid-level"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/object-pose-estimation-using-mid-level-visual","title":"Object Pose Estimation using Mid-level Visual Representations","date":"2022-03-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/holistic-3d-scene-understanding-from-a-single-1","title":"Holistic 3D Scene Understanding from a Single Image with Implicit Representation","date":"2021-03-11","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/total3dunderstanding-joint-layout-object-pose","title":"Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image","date":"2020-02-27","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":2,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deep-mesh-reconstruction-from-single-rgb","title":"Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networks","date":"2019-09-01","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":1,"samples_unverified":11,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/mesh-r-cnn","title":"Mesh R-CNN","date":"2019-06-06","rows_on_this_dataset":2,"code_links":7,"syntology":null},{"paper":"/paper/pix3d-dataset-and-methods-for-single-image-3d","title":"Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling","date":"2018-04-12","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/atlasnet-a-papier-mache-approach-to-learning","title":"AtlasNet: A Papier-Mâché Approach to Learning 3D Surface Generation","date":"2018-02-15","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":3,"samples_unverified":0,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/marrnet-3d-shape-reconstruction-via-25d","title":"MarrNet: 3D Shape Reconstruction via 2.5D Sketches","date":"2017-11-08","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/learning-a-probabilistic-latent-space-of","title":"Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling","date":"2016-10-24","rows_on_this_dataset":1,"code_links":3,"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; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":27,"samples_ran":9,"samples_unverified":18,"pointer_only_for_licence":3,"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."}