{"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/taking-a-deeper-look-at-the-inverse","title":"Taking a Deeper Look at the Inverse Compositional Algorithm","arxiv_id":"1812.06861","date":"2018-12-17","proceeding":"CVPR 2019 6","authors":["Zhaoyang Lv","Frank Dellaert","James M. Rehg","Andreas Geiger"],"abstract":"In this paper, we provide a modern synthesis of the classic inverse\ncompositional algorithm for dense image alignment. We first discuss the\nassumptions made by this well-established technique, and subsequently propose\nto relax these assumptions by incorporating data-driven priors into this model.\nMore specifically, we unroll a robust version of the inverse compositional\nalgorithm and replace multiple components of this algorithm using more\nexpressive models whose parameters we train in an end-to-end fashion from data.\nOur experiments on several challenging 3D rigid motion estimation tasks\ndemonstrate the advantages of combining optimization with learning-based\ntechniques, outperforming the classic inverse compositional algorithm as well\nas data-driven image-to-pose regression approaches.","url_abs":"http://arxiv.org/abs/1812.06861v2","url_pdf":"http://arxiv.org/pdf/1812.06861v2.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":"taking-a-deeper-look-at-the-inverse","repo_url":"https://github.com/lvzhaoyang/DeeperInverseCompositionalAlgorithm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"motion-estimation","task_name":"Motion Estimation"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1812.06861","atlas_url":"https://app.syntology.ai/?focus=1812.06861","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1812.06861"}},"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/lvzhaoyang/DeeperInverseCompositionalAlgorithm","reach":null}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{"official":{"samples":1,"ran":1,"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":"ba52ef2328523dc5","entry":"eval_trajectories","repo":"lvzhaoyang/DeeperInverseCompositionalAlgorithm","repo_kind":"official","path":"code/evaluate.py","file_url":"https://github.com/lvzhaoyang/DeeperInverseCompositionalAlgorithm/blob/HEAD/code/evaluate.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":"ba52ef2328523dc5"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}