{"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/no-fear-of-the-dark-image-retrieval-under","title":"No Fear of the Dark: Image Retrieval under Varying Illumination Conditions","arxiv_id":"1908.08999","date":"2019-08-23","proceeding":"ICCV 2019 10","authors":["Tomas Jenicek","Ondřej Chum"],"abstract":"Image retrieval under varying illumination conditions, such as day and night images, is addressed by image preprocessing, both hand-crafted and learned. Prior to extracting image descriptors by a convolutional neural network, images are photometrically normalised in order to reduce the descriptor sensitivity to illumination changes. We propose a learnable normalisation based on the U-Net architecture, which is trained on a combination of single-camera multi-exposure images and a newly constructed collection of similar views of landmarks during day and night. We experimentally show that both hand-crafted normalisation based on local histogram equalisation and the learnable normalisation outperform standard approaches in varying illumination conditions, while staying on par with the state-of-the-art methods on daylight illumination benchmarks, such as Oxford or Paris datasets.","url_abs":"https://arxiv.org/abs/1908.08999v1","url_pdf":"https://arxiv.org/pdf/1908.08999v1.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":"no-fear-of-the-dark-image-retrieval-under","repo_url":"https://github.com/jenicek/mdir","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"image-retrieval","task_name":"Image Retrieval"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[{"method_slug":"concatenated-skip-connection","method_name":"Concatenated Skip Connection"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"u-net","method_name":"U-Net"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/image-retrieval-on-24-7-tokyo","task":"Image Retrieval","dataset":"24/7 Tokyo","model":"CLAHE","rank_in_archive_order":3,"of":3,"metrics":{"mAP":"87.0"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1908.08999","atlas_url":"https://app.syntology.ai/?focus=1908.08999","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.08999"}},"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":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jenicek/mdir","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":7},"by_repo_kind":{"official":{"samples":7,"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":"482dc3381dc53dd1","entry":"he_normal_","repo":"jenicek/mdir","repo_kind":"official","path":"mdir/components/model/weight_initialization.py","file_url":"https://github.com/jenicek/mdir/blob/HEAD/mdir/components/model/weight_initialization.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":"482dc3381dc53dd1"}},{"code_sha256_prefix":"53551ea3ec567486","entry":"infer","repo":"jenicek/mdir","repo_kind":"official","path":"mdir/stages/infer.py","file_url":"https://github.com/jenicek/mdir/blob/HEAD/mdir/stages/infer.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":"53551ea3ec567486"}},{"code_sha256_prefix":"edae4d5d5b385d62","entry":"initialize_epoch_iteration","repo":"jenicek/mdir","repo_kind":"official","path":"mdir/learning/epoch_iteration.py","file_url":"https://github.com/jenicek/mdir/blob/HEAD/mdir/learning/epoch_iteration.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":"edae4d5d5b385d62"}},{"code_sha256_prefix":"b823434e578c79a4","entry":"initialize_network","repo":"jenicek/mdir","repo_kind":"official","path":"mdir/learning/network.py","file_url":"https://github.com/jenicek/mdir/blob/HEAD/mdir/learning/network.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":"b823434e578c79a4"}},{"code_sha256_prefix":"cebb39b7bae53f34","entry":"initialize_training","repo":"jenicek/mdir","repo_kind":"official","path":"mdir/learning/training.py","file_url":"https://github.com/jenicek/mdir/blob/HEAD/mdir/learning/training.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":"cebb39b7bae53f34"}},{"code_sha256_prefix":"3ab97b38a53bdc1c","entry":"initialize_validation","repo":"jenicek/mdir","repo_kind":"official","path":"mdir/learning/validation.py","file_url":"https://github.com/jenicek/mdir/blob/HEAD/mdir/learning/validation.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":"3ab97b38a53bdc1c"}},{"code_sha256_prefix":"7504e6e491aca0d4","entry":"validate","repo":"jenicek/mdir","repo_kind":"official","path":"mdir/stages/validate.py","file_url":"https://github.com/jenicek/mdir/blob/HEAD/mdir/stages/validate.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":"7504e6e491aca0d4"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}