{"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/dwt-init","entry":"dwt_init","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":6,"n_papers_ran":4,"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":3,"n_samples_fingerprinted":3,"n_places":6,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":3,"unverified":2},"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":"2508.02168","paper":"/paper/arxiv-2508-02168","title":"After the Party: Navigating the Mapping From Color to Ambient Lighting","date":null,"month_inferred_from_arxiv_id":"2025-08","title_source":"syntology","repo":"fvasluianu97/RLN2","path":"basicsr/models/archs/cc36_arch.py","file_url":"https://github.com/fvasluianu97/RLN2/blob/HEAD/basicsr/models/archs/cc36_arch.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"cea593bd1130769e","mcp_get_code":{"code_sha256":"cea593bd1130769e"}},{"arxiv_id":"2405.09873","paper":"/paper/irsrmamba-infrared-image-super-resolution-via","title":"IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model","date":"2024-05-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yongsongh/irsrmamba","path":"basicsr/archs/irsrmamba_arch.py","file_url":"https://github.com/yongsongh/irsrmamba/blob/HEAD/basicsr/archs/irsrmamba_arch.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"c21c44ba4d3c7c73","mcp_get_code":{"code_sha256":"c21c44ba4d3c7c73"}},{"arxiv_id":"2402.12192","paper":"/paper/pan-mamba-effective-pan-sharpening-with-state","title":"Pan-Mamba: Effective pan-sharpening with State Space Model","date":"2024-02-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alexhe101/pan-mamba","path":"pan-sharpening/model/dwte.py","file_url":"https://github.com/alexhe101/pan-mamba/blob/HEAD/pan-sharpening/model/dwte.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0f828f7a883480ec","mcp_get_code":{"code_sha256":"0f828f7a883480ec"}},{"arxiv_id":"2311.16845","paper":"/paper/wavelet-based-fourier-information-interaction","title":"Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restoration","date":"2023-11-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhihefang/wf-diff","path":"basicsr/models/Wfdiff_model.py","file_url":"https://github.com/zhihefang/wf-diff/blob/HEAD/basicsr/models/Wfdiff_model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c772979b10e50aa7","mcp_get_code":{"code_sha256":"c772979b10e50aa7"}},{"arxiv_id":"2306.00306","paper":"/paper/low-light-image-enhancement-with-wavelet","title":"Low-Light Image Enhancement with Wavelet-based Diffusion Models","date":"2023-06-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"JianghaiSCU/Diffusion-Low-Light","path":"models/wavelet.py","file_url":"https://github.com/JianghaiSCU/Diffusion-Low-Light/blob/HEAD/models/wavelet.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c772979b10e50aa7","mcp_get_code":{"code_sha256":"c772979b10e50aa7"}},{"arxiv_id":"2204.08397","paper":"/paper/fast-and-memory-efficient-network-towards","title":"Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution","date":"2022-04-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Gaurav14cs17/Reparameterization-Denoising","path":"models/MFDNet.py","file_url":"https://github.com/Gaurav14cs17/Reparameterization-Denoising/blob/HEAD/models/MFDNet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e1fc3727aabb3df4","mcp_get_code":{"code_sha256":"e1fc3727aabb3df4"}}]}