{"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/faster-gaze-prediction-with-dense-networks","title":"Faster gaze prediction with dense networks and Fisher pruning","arxiv_id":"1801.05787","date":"2018-01-17","proceeding":"Twitter 2018 1","authors":["Lucas Theis","Iryna Korshunova","Alykhan Tejani","Ferenc Huszár"],"abstract":"Predicting human fixations from images has recently seen large improvements\nby leveraging deep representations which were pretrained for object\nrecognition. However, as we show in this paper, these networks are highly\noverparameterized for the task of fixation prediction. We first present a\nsimple yet principled greedy pruning method which we call Fisher pruning.\nThrough a combination of knowledge distillation and Fisher pruning, we obtain\nmuch more runtime-efficient architectures for saliency prediction, achieving a\n10x speedup for the same AUC performance as a state of the art network on the\nCAT2000 dataset. Speeding up single-image gaze prediction is important for many\nreal-world applications, but it is also a crucial step in the development of\nvideo saliency models, where the amount of data to be processed is\nsubstantially larger.","url_abs":"http://arxiv.org/abs/1801.05787v2","url_pdf":"http://arxiv.org/pdf/1801.05787v2.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":"faster-gaze-prediction-with-dense-networks","repo_url":"https://github.com/EkdeepSLubana/OrthoReg","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"faster-gaze-prediction-with-dense-networks","repo_url":"https://github.com/the-super-toys/glimpse-models","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"gaze-estimation","task_name":"Gaze Estimation"},{"task_slug":"eye-tracking","task_name":"Gaze Prediction"},{"task_slug":"knowledge-distillation","task_name":"Knowledge Distillation"},{"task_slug":"object-recognition","task_name":"Object Recognition"},{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"saliency-prediction","task_name":"Saliency Prediction"}],"methods":[{"method_slug":"knowledge-distillation","method_name":"Knowledge Distillation"},{"method_slug":"pruning","method_name":"Pruning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1801.05787","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1801.05787"}},"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/EkdeepSLubana/OrthoReg","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/the-super-toys/glimpse-models","reach":{"status":"unanswered"}}],"summary":{"ran_draft_wrong":3},"by_repo_kind":{"listed":{"samples":3,"ran":3,"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":"d741770c08c6d1c1","entry":"ResPruned","repo":"EkdeepSLubana/OrthoReg","repo_kind":"listed","path":"pruner.py","file_url":"https://github.com/EkdeepSLubana/OrthoReg/blob/HEAD/pruner.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d741770c08c6d1c1"}},{"code_sha256_prefix":"daa1576df793359a","entry":"ResPruned_cifar","repo":"EkdeepSLubana/OrthoReg","repo_kind":"listed","path":"pruner.py","file_url":"https://github.com/EkdeepSLubana/OrthoReg/blob/HEAD/pruner.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"daa1576df793359a"}},{"code_sha256_prefix":"da059431c1f96fc2","entry":"constrain_ratios","repo":"EkdeepSLubana/OrthoReg","repo_kind":"listed","path":"pruner.py","file_url":"https://github.com/EkdeepSLubana/OrthoReg/blob/HEAD/pruner.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"da059431c1f96fc2"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}