{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:AYWPGEJUT7G24C4QMHGUR7OVHZ","short_pith_number":"pith:AYWPGEJU","schema_version":"1.0","canonical_sha256":"062cf311349fcdae0b9061cd48fdd53e43cda060874e3146e6d9019f67506fe1","source":{"kind":"arxiv","id":"1910.14218","version":1},"attestation_state":"computed","paper":{"title":"S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Hao Su, Hao Zhu, Jing Xu, Meng Song, Rui Chen, Yuzhe Qin","submitted_at":"2019-10-31T02:29:57Z","abstract_excerpt":"Grasping is among the most fundamental and long-lasting problems in robotics study. This paper studies the problem of 6-DoF(degree of freedom) grasping by a parallel gripper in a cluttered scene captured using a commodity depth sensor from a single viewpoint. We address the problem in a learning-based framework. At the high level, we rely on a single-shot grasp proposal network, trained with synthetic data and tested in real-world scenarios. Our single-shot neural network architecture can predict amodal grasp proposal efficiently and effectively. Our training data synthesis pipeline can genera"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1910.14218","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2019-10-31T02:29:57Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"838c708a48b1ba35148d18519f8623a0f9f92102728ce37a3e6b727b21fe06b2","abstract_canon_sha256":"fd125fc6af075eb0bd79b6bd60e279387f8e80ee40ba1a60af021dda7587ddab"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:16:08.664590Z","signature_b64":"SAFa7P35Dsy9r0AEXR6BIfvLJTLnWvoz+8yW/ybGXTfqzIfY0dAVRTIGwvZf2G3H9187D/SxiW9IVh+i2dcxAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"062cf311349fcdae0b9061cd48fdd53e43cda060874e3146e6d9019f67506fe1","last_reissued_at":"2026-07-05T00:16:08.664170Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:16:08.664170Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Hao Su, Hao Zhu, Jing Xu, Meng Song, Rui Chen, Yuzhe Qin","submitted_at":"2019-10-31T02:29:57Z","abstract_excerpt":"Grasping is among the most fundamental and long-lasting problems in robotics study. This paper studies the problem of 6-DoF(degree of freedom) grasping by a parallel gripper in a cluttered scene captured using a commodity depth sensor from a single viewpoint. We address the problem in a learning-based framework. At the high level, we rely on a single-shot grasp proposal network, trained with synthetic data and tested in real-world scenarios. Our single-shot neural network architecture can predict amodal grasp proposal efficiently and effectively. Our training data synthesis pipeline can genera"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.14218","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1910.14218/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1910.14218","created_at":"2026-07-05T00:16:08.664226+00:00"},{"alias_kind":"arxiv_version","alias_value":"1910.14218v1","created_at":"2026-07-05T00:16:08.664226+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.14218","created_at":"2026-07-05T00:16:08.664226+00:00"},{"alias_kind":"pith_short_12","alias_value":"AYWPGEJUT7G2","created_at":"2026-07-05T00:16:08.664226+00:00"},{"alias_kind":"pith_short_16","alias_value":"AYWPGEJUT7G24C4Q","created_at":"2026-07-05T00:16:08.664226+00:00"},{"alias_kind":"pith_short_8","alias_value":"AYWPGEJU","created_at":"2026-07-05T00:16:08.664226+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ","json":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ.json","graph_json":"https://pith.science/api/pith-number/AYWPGEJUT7G24C4QMHGUR7OVHZ/graph.json","events_json":"https://pith.science/api/pith-number/AYWPGEJUT7G24C4QMHGUR7OVHZ/events.json","paper":"https://pith.science/paper/AYWPGEJU"},"agent_actions":{"view_html":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ","download_json":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ.json","view_paper":"https://pith.science/paper/AYWPGEJU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1910.14218&json=true","fetch_graph":"https://pith.science/api/pith-number/AYWPGEJUT7G24C4QMHGUR7OVHZ/graph.json","fetch_events":"https://pith.science/api/pith-number/AYWPGEJUT7G24C4QMHGUR7OVHZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ/action/storage_attestation","attest_author":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ/action/author_attestation","sign_citation":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ/action/citation_signature","submit_replication":"https://pith.science/pith/AYWPGEJUT7G24C4QMHGUR7OVHZ/action/replication_record"}},"created_at":"2026-07-05T00:16:08.664226+00:00","updated_at":"2026-07-05T00:16:08.664226+00:00"}