{"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/what-can-simple-arithmetic-operations-do-for","title":"What Can Simple Arithmetic Operations Do for Temporal Modeling?","arxiv_id":"2307.08908","date":"2023-07-18","proceeding":"ICCV 2023 1","authors":["Wenhao Wu","Yuxin Song","Zhun Sun","Jingdong Wang","Chang Xu","Wanli Ouyang"],"abstract":"Temporal modeling plays a crucial role in understanding video content. To tackle this problem, previous studies built complicated temporal relations through time sequence thanks to the development of computationally powerful devices. In this work, we explore the potential of four simple arithmetic operations for temporal modeling. Specifically, we first capture auxiliary temporal cues by computing addition, subtraction, multiplication, and division between pairs of extracted frame features. Then, we extract corresponding features from these cues to benefit the original temporal-irrespective domain. We term such a simple pipeline as an Arithmetic Temporal Module (ATM), which operates on the stem of a visual backbone with a plug-and-play style. We conduct comprehensive ablation studies on the instantiation of ATMs and demonstrate that this module provides powerful temporal modeling capability at a low computational cost. Moreover, the ATM is compatible with both CNNs- and ViTs-based architectures. Our results show that ATM achieves superior performance over several popular video benchmarks. Specifically, on Something-Something V1, V2 and Kinetics-400, we reach top-1 accuracy of 65.6%, 74.6%, and 89.4% respectively. The code is available at https://github.com/whwu95/ATM.","url_abs":"https://arxiv.org/abs/2307.08908v2","url_pdf":"https://arxiv.org/pdf/2307.08908v2.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":"what-can-simple-arithmetic-operations-do-for","repo_url":"https://github.com/whwu95/ATM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"what-can-simple-arithmetic-operations-do-for","repo_url":"https://github.com/HJYao00/Side4Video","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"action-classification","task_name":"Action Classification"},{"task_slug":"action-recognition-in-videos","task_name":"Action Recognition"},{"task_slug":"video-recognition","task_name":"Video Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/action-classification-on-kinetics-400","task":"Action Classification","dataset":"Kinetics-400","model":"ATM","rank_in_archive_order":18,"of":207,"metrics":{"Acc@1":"89.4","Acc@5":"98.3"},"uses_additional_data":false},{"leaderboard":"/sota/action-recognition-in-videos-on-something-1","task":"Action Recognition","dataset":"Something-Something V1","model":"ATM","rank_in_archive_order":4,"of":74,"metrics":{"Top 1 Accuracy":"65.6","Top 5 Accuracy":"88.6"},"uses_additional_data":false},{"leaderboard":"/sota/action-recognition-in-videos-on-something","task":"Action Recognition","dataset":"Something-Something V2","model":"ATM","rank_in_archive_order":13,"of":123,"metrics":{"Top-1 Accuracy":"74.6","Top-5 Accuracy":"94.4"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2307.08908","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.08908"}},"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":"deterministic:regex_extraction","url":"https://github.com/whwu95/ATM","reach":null}],"summary":{"ran":3,"unverified":3},"by_repo_kind":{"official":{"samples":6,"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":"252ed3e3ac78c561","entry":"Conv2D_UV2C","repo":"whwu95/ATM","repo_kind":"official","path":"modules/ATM.py","file_url":"https://github.com/whwu95/ATM/blob/HEAD/modules/ATM.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":"252ed3e3ac78c561"}},{"code_sha256_prefix":"4c4d884517c1250d","entry":"DiffBlock","repo":"whwu95/ATM","repo_kind":"official","path":"modules/ATM.py","file_url":"https://github.com/whwu95/ATM/blob/HEAD/modules/ATM.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":"4c4d884517c1250d"}},{"code_sha256_prefix":"bc490bc7c211e0c1","entry":"DomainTransfer","repo":"whwu95/ATM","repo_kind":"official","path":"modules/ATM.py","file_url":"https://github.com/whwu95/ATM/blob/HEAD/modules/ATM.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":"bc490bc7c211e0c1"}},{"code_sha256_prefix":"84a9fb91857b60cf","entry":"ATMBlock","repo":"whwu95/ATM","repo_kind":"official","path":"modules/ATM.py","file_url":"https://github.com/whwu95/ATM/blob/HEAD/modules/ATM.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":"84a9fb91857b60cf"}},{"code_sha256_prefix":"17fe85569ab1f3e9","entry":"SimBlock","repo":"whwu95/ATM","repo_kind":"official","path":"modules/ATM.py","file_url":"https://github.com/whwu95/ATM/blob/HEAD/modules/ATM.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":"17fe85569ab1f3e9"}},{"code_sha256_prefix":"4faabb379a6b7d0c","entry":"SimTransform","repo":"whwu95/ATM","repo_kind":"official","path":"modules/ATM.py","file_url":"https://github.com/whwu95/ATM/blob/HEAD/modules/ATM.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":"4faabb379a6b7d0c"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}