{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pano3d-a-holistic-benchmark-and-a-solid","title":"Pano3D: A Holistic Benchmark and a Solid Baseline for $360^o$ Depth Estimation","arxiv_id":"2109.02749","date":"2021-09-06","proceeding":null,"authors":["Georgios Albanis","Nikolaos Zioulis","Petros Drakoulis","Vasileios Gkitsas","Vladimiros Sterzentsenko","Federico Alvarez","Dimitrios Zarpalas","Petros Daras"],"abstract":"Pano3D is a new benchmark for depth estimation from spherical panoramas. It aims to assess performance across all depth estimation traits, the primary direct depth estimation performance targeting precision and accuracy, and also the secondary traits, boundary preservation, and smoothness. Moreover, Pano3D moves beyond typical intra-dataset evaluation to inter-dataset performance assessment. By disentangling the capacity to generalize to unseen data into different test splits, Pano3D represents a holistic benchmark for $360^o$ depth estimation. We use it as a basis for an extended analysis seeking to offer insights into classical choices for depth estimation. This results in a solid baseline for panoramic depth that follow-up works can build upon to steer future progress.","url_abs":"https://arxiv.org/abs/2109.02749v1","url_pdf":"https://arxiv.org/pdf/2109.02749v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pano3d-a-holistic-benchmark-and-a-solid","repo_url":"https://github.com/VCL3D/Pano3D","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"depth-estimation","task_name":"Depth Estimation"}],"methods":[],"datasets_introduced":[{"slug":"pano3d","name":"Pano3D","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2109.02749","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.02749"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/VCL3D/Pano3D","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":3},"by_repo_kind":{"official":{"samples":3,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"23c174281e2b9f43","entry":"load_color","repo":"VCL3D/Pano3D","repo_kind":"official","path":"pano3d/dataset/loaders.py","file_url":"https://github.com/VCL3D/Pano3D/blob/HEAD/pano3d/dataset/loaders.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"23c174281e2b9f43"}},{"code_sha256_prefix":"b56a7f87698badf0","entry":"load_depth","repo":"VCL3D/Pano3D","repo_kind":"official","path":"pano3d/dataset/loaders.py","file_url":"https://github.com/VCL3D/Pano3D/blob/HEAD/pano3d/dataset/loaders.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b56a7f87698badf0"}},{"code_sha256_prefix":"193fb34c55eec29f","entry":"load_normal","repo":"VCL3D/Pano3D","repo_kind":"official","path":"pano3d/dataset/loaders.py","file_url":"https://github.com/VCL3D/Pano3D/blob/HEAD/pano3d/dataset/loaders.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"193fb34c55eec29f"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}