{"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/equivariant-descriptor-fields-se-3","title":"Equivariant Descriptor Fields: SE(3)-Equivariant Energy-Based Models for End-to-End Visual Robotic Manipulation Learning","arxiv_id":"2206.08321","date":"2022-06-16","proceeding":null,"authors":["Hyunwoo Ryu","Hong-in Lee","Jeong-Hoon Lee","Jongeun Choi"],"abstract":"End-to-end learning for visual robotic manipulation is known to suffer from sample inefficiency, requiring large numbers of demonstrations. The spatial roto-translation equivariance, or the SE(3)-equivariance can be exploited to improve the sample efficiency for learning robotic manipulation. In this paper, we present SE(3)-equivariant models for visual robotic manipulation from point clouds that can be trained fully end-to-end. By utilizing the representation theory of the Lie group, we construct novel SE(3)-equivariant energy-based models that allow highly sample efficient end-to-end learning. We show that our models can learn from scratch without prior knowledge and yet are highly sample efficient (5~10 demonstrations are enough). Furthermore, we show that our models can generalize to tasks with (i) previously unseen target object poses, (ii) previously unseen target object instances of the category, and (iii) previously unseen visual distractors. We experiment with 6-DoF robotic manipulation tasks to validate our models' sample efficiency and generalizability. Codes are available at: https://github.com/tomato1mule/edf","url_abs":"https://arxiv.org/abs/2206.08321v3","url_pdf":"https://arxiv.org/pdf/2206.08321v3.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":"equivariant-descriptor-fields-se-3","repo_url":"https://github.com/tomato1mule/edf","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2206.08321","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.08321"}},"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/tomato1mule/edf","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":"a152d45a718f2b4f","entry":"binomial_test","repo":"tomato1mule/edf","repo_kind":"official","path":"edf/utils.py","file_url":"https://github.com/tomato1mule/edf/blob/HEAD/edf/utils.py","link_basis":"harvester_set","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":"a152d45a718f2b4f"}},{"code_sha256_prefix":"a43e13b397e725b6","entry":"check_irreps_sorted","repo":"tomato1mule/edf","repo_kind":"official","path":"edf/utils.py","file_url":"https://github.com/tomato1mule/edf/blob/HEAD/edf/utils.py","link_basis":"harvester_set","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":"a43e13b397e725b6"}},{"code_sha256_prefix":"6c2137047bd71ed5","entry":"gaussian_kernels","repo":"tomato1mule/edf","repo_kind":"official","path":"edf/layers.py","file_url":"https://github.com/tomato1mule/edf/blob/HEAD/edf/layers.py","link_basis":"harvester_set","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":"6c2137047bd71ed5"}},{"code_sha256_prefix":"1b623741867192ee","entry":"gzip_load","repo":"tomato1mule/edf","repo_kind":"official","path":"edf/data.py","file_url":"https://github.com/tomato1mule/edf/blob/HEAD/edf/data.py","link_basis":"harvester_set","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":"1b623741867192ee"}},{"code_sha256_prefix":"4883c352c5a1abf8","entry":"load_yaml","repo":"tomato1mule/edf","repo_kind":"official","path":"edf/data.py","file_url":"https://github.com/tomato1mule/edf/blob/HEAD/edf/data.py","link_basis":"harvester_set","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":"4883c352c5a1abf8"}},{"code_sha256_prefix":"3c99f35f52f28eb4","entry":"soft_cutoff","repo":"tomato1mule/edf","repo_kind":"official","path":"edf/layers.py","file_url":"https://github.com/tomato1mule/edf/blob/HEAD/edf/layers.py","link_basis":"harvester_set","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":"3c99f35f52f28eb4"}},{"code_sha256_prefix":"321d15c3c173d3bd","entry":"soft_step","repo":"tomato1mule/edf","repo_kind":"official","path":"edf/layers.py","file_url":"https://github.com/tomato1mule/edf/blob/HEAD/edf/layers.py","link_basis":"harvester_set","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":"321d15c3c173d3bd"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}