{"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":"/code/conical-frustum-to-gaussian","entry":"conical_frustum_to_gaussian","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":5,"n_papers_ran":1,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":5,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":4},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2308.13404","paper":"/paper/relighting-neural-radiance-fields-with-shadow","title":"Relighting Neural Radiance Fields with Shadow and Highlight Hints","date":"2023-08-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"iamNCJ/NRHints","path":"camera/ray_utils.py","file_url":"https://github.com/iamNCJ/NRHints/blob/HEAD/camera/ray_utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"9ef31786380a0afc","mcp_get_code":{"code_sha256":"9ef31786380a0afc"}},{"arxiv_id":"2304.07743","paper":"/paper/seathru-nerf-neural-radiance-fields-in","title":"SeaThru-NeRF: Neural Radiance Fields in Scattering Media","date":"2023-04-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"deborahLevy130/seathru_NeRF","path":"internal/render.py","file_url":"https://github.com/deborahLevy130/seathru_NeRF/blob/HEAD/internal/render.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"8ff2578b6f10edd0","mcp_get_code":{"code_sha256":"8ff2578b6f10edd0"}},{"arxiv_id":"2303.13817","paper":"/paper/able-nerf-attention-based-rendering-with","title":"ABLE-NeRF: Attention-Based Rendering with Learnable Embeddings for Neural Radiance Field","date":"2023-03-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"TangZJ/able-nerf","path":"models/able_nerf.py","file_url":"https://github.com/TangZJ/able-nerf/blob/HEAD/models/able_nerf.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3b22ae6dad1741a0","mcp_get_code":{"code_sha256":"3b22ae6dad1741a0"}},{"arxiv_id":"2211.12285","paper":"/paper/exact-nerf-an-exploration-of-a-precise","title":"Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields","date":"2022-11-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kostadinovshalon/exact-nerf","path":"internal/render.py","file_url":"https://github.com/kostadinovshalon/exact-nerf/blob/HEAD/internal/render.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"52da3923171d06b7","mcp_get_code":{"code_sha256":"52da3923171d06b7"}},{"arxiv_id":"2103.13415","paper":"/paper/mip-nerf-a-multiscale-representation-for-anti","title":"Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields","date":"2021-03-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bebeal/mipnerf-pytorch","path":"model.py","file_url":"https://github.com/bebeal/mipnerf-pytorch/blob/HEAD/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c9d6592f49f2731a","mcp_get_code":{"code_sha256":"c9d6592f49f2731a"}}]}