{"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/simulating-dual-pixel-images-from-ray-tracing","title":"Simulating Dual-Pixel Images From Ray Tracing For Depth Estimation","arxiv_id":"2503.11213","date":"2025-03-14","proceeding":null,"authors":["Fengchen He","Dayang Zhao","Hao Xu","Tingwei Quan","Shaoqun Zeng"],"abstract":"Many studies utilize dual-pixel (DP) sensor phase characteristics for various applications, such as depth estimation and deblurring. However, since the DP image features are entirely determined by the camera hardware, DP-depth paired datasets are very scarce, especially when performing depth estimation on customized cameras. To overcome this, studies simulate DP images using ideal optical system models. However, these simulations often violate real optical propagation laws,leading to poor generalization to real DP data. To address this, we investigate the domain gap between simulated and real DP data, and propose solutions using the Simulating DP images from ray tracing (Sdirt) scheme. The Sdirt generates realistic DP images via ray tracing and integrates them into the depth estimation training pipeline. Experimental results show that models trained with Sdirt-simulated images generalize better to real DP data.","url_abs":"https://arxiv.org/abs/2503.11213v1","url_pdf":"https://arxiv.org/pdf/2503.11213v1.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":"simulating-dual-pixel-images-from-ray-tracing","repo_url":"https://github.com/LinYark/Sdirt","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"deblurring","task_name":"Deblurring"},{"task_slug":"depth-estimation","task_name":"Depth Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2503.11213","atlas_url":"https://app.syntology.ai/?focus=2503.11213","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.11213"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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":"deterministic:regex_extraction","url":"https://github.com/LinYark/Sdirt","reach":null}],"summary":{"ran":3,"ran_draft_wrong":1,"unverified":4},"by_repo_kind":{"official":{"samples":8,"ran":4,"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":"379600b503a1a265","entry":"BasicConv","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"379600b503a1a265"}},{"code_sha256_prefix":"83cd69473fcbd26b","entry":"Conv2x","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"83cd69473fcbd26b"}},{"code_sha256_prefix":"0bd1d9b075e0897b","entry":"Feature","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"0bd1d9b075e0897b"}},{"code_sha256_prefix":"5062860b9b0d2850","entry":"convbn","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5062860b9b0d2850"}},{"code_sha256_prefix":"076cdae12a76cc0f","entry":"Disp","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.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":"076cdae12a76cc0f"}},{"code_sha256_prefix":"90b93d1c10c796f6","entry":"DisparityRegression","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.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":"90b93d1c10c796f6"}},{"code_sha256_prefix":"22c6468c78ba3aae","entry":"Matching","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.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":"22c6468c78ba3aae"}},{"code_sha256_prefix":"4cd5d444097eef75","entry":"YRStereonet_3D","repo":"LinYark/Sdirt","repo_kind":"official","path":"dfdp/dddnet/dddnet.py","file_url":"https://github.com/LinYark/Sdirt/blob/HEAD/dfdp/dddnet/dddnet.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":"4cd5d444097eef75"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}