{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:LLEVVRTQWYPE6XXOO3MEWS2UEI","short_pith_number":"pith:LLEVVRTQ","canonical_record":{"source":{"id":"1903.09761","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-23T05:05:22Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"15ed8ce84cf487baf5081c08ad91632d511cc77748d9c01cbb767d2a86980b9b","abstract_canon_sha256":"ecbcefb1f8a23a389fa48a38126222431cfa9f927aacbe10755c64ab18924bd7"},"schema_version":"1.0"},"canonical_sha256":"5ac95ac670b61e4f5eee76d84b4b542237968100ac598ab4a7a3425a647b4efa","source":{"kind":"arxiv","id":"1903.09761","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.09761","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"arxiv_version","alias_value":"1903.09761v1","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.09761","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"pith_short_12","alias_value":"LLEVVRTQWYPE","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"LLEVVRTQWYPE6XXO","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"LLEVVRTQ","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:LLEVVRTQWYPE6XXOO3MEWS2UEI","target":"record","payload":{"canonical_record":{"source":{"id":"1903.09761","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-23T05:05:22Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"15ed8ce84cf487baf5081c08ad91632d511cc77748d9c01cbb767d2a86980b9b","abstract_canon_sha256":"ecbcefb1f8a23a389fa48a38126222431cfa9f927aacbe10755c64ab18924bd7"},"schema_version":"1.0"},"canonical_sha256":"5ac95ac670b61e4f5eee76d84b4b542237968100ac598ab4a7a3425a647b4efa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:50:35.577225Z","signature_b64":"UdqsV05VEzKYlgu9yac6NkdOH5Up2SWymyEaDb9DhShO3h25A4ePFPU6d93uRDe0TY2wgsZ3t5Mqd5nP19qYCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5ac95ac670b61e4f5eee76d84b4b542237968100ac598ab4a7a3425a647b4efa","last_reissued_at":"2026-05-17T23:50:35.576445Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:50:35.576445Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.09761","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:50:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c8WtZ/FICaTwg0YWwtQSc+aDLpwpgw8Nv0UqMvsi/JnOK+tKNkPK2SV+93mFqwkwKH2KP349bwI3pU2YQa+/Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T15:49:39.332244Z"},"content_sha256":"29130f69a6ee05552591ba7bc7f3821f76110134eacf55f84b6592fc63e0444e","schema_version":"1.0","event_id":"sha256:29130f69a6ee05552591ba7bc7f3821f76110134eacf55f84b6592fc63e0444e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:LLEVVRTQWYPE6XXOO3MEWS2UEI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scene Understanding for Autonomous Manipulation with Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Anh Nguyen","submitted_at":"2019-03-23T05:05:22Z","abstract_excerpt":"Over the past few years, deep learning techniques have achieved tremendous success in many visual understanding tasks such as object detection, image segmentation, and caption generation. Despite this thriving in computer vision and natural language processing, deep learning has not yet shown significant impact in robotics. Due to the gap between theory and application, there are many challenges when applying the results of deep learning to the real robotic systems. In this study, our long-term goal is to bridge the gap between computer vision and robotics by developing visual methods that can"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.09761","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:50:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iNqrJ3eLO5n0yt01nEEsNQrH58R79CTLUHQ+TRHXB4NQvQk7/n8ftRI8vbL1iwOXxZfwtKo96l5vXUGiY3slCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T15:49:39.332604Z"},"content_sha256":"b708b4f01c628c911c534c59c138e49190f6653040ebd09cea4fd46fe04d9894","schema_version":"1.0","event_id":"sha256:b708b4f01c628c911c534c59c138e49190f6653040ebd09cea4fd46fe04d9894"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LLEVVRTQWYPE6XXOO3MEWS2UEI/bundle.json","state_url":"https://pith.science/pith/LLEVVRTQWYPE6XXOO3MEWS2UEI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LLEVVRTQWYPE6XXOO3MEWS2UEI/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-03T15:49:39Z","links":{"resolver":"https://pith.science/pith/LLEVVRTQWYPE6XXOO3MEWS2UEI","bundle":"https://pith.science/pith/LLEVVRTQWYPE6XXOO3MEWS2UEI/bundle.json","state":"https://pith.science/pith/LLEVVRTQWYPE6XXOO3MEWS2UEI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LLEVVRTQWYPE6XXOO3MEWS2UEI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:LLEVVRTQWYPE6XXOO3MEWS2UEI","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"ecbcefb1f8a23a389fa48a38126222431cfa9f927aacbe10755c64ab18924bd7","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-23T05:05:22Z","title_canon_sha256":"15ed8ce84cf487baf5081c08ad91632d511cc77748d9c01cbb767d2a86980b9b"},"schema_version":"1.0","source":{"id":"1903.09761","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.09761","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"arxiv_version","alias_value":"1903.09761v1","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.09761","created_at":"2026-05-17T23:50:35Z"},{"alias_kind":"pith_short_12","alias_value":"LLEVVRTQWYPE","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"LLEVVRTQWYPE6XXO","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"LLEVVRTQ","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:b708b4f01c628c911c534c59c138e49190f6653040ebd09cea4fd46fe04d9894","target":"graph","created_at":"2026-05-17T23:50:35Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Over the past few years, deep learning techniques have achieved tremendous success in many visual understanding tasks such as object detection, image segmentation, and caption generation. Despite this thriving in computer vision and natural language processing, deep learning has not yet shown significant impact in robotics. Due to the gap between theory and application, there are many challenges when applying the results of deep learning to the real robotic systems. In this study, our long-term goal is to bridge the gap between computer vision and robotics by developing visual methods that can","authors_text":"Anh Nguyen","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-23T05:05:22Z","title":"Scene Understanding for Autonomous Manipulation with Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.09761","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:29130f69a6ee05552591ba7bc7f3821f76110134eacf55f84b6592fc63e0444e","target":"record","created_at":"2026-05-17T23:50:35Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"ecbcefb1f8a23a389fa48a38126222431cfa9f927aacbe10755c64ab18924bd7","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-03-23T05:05:22Z","title_canon_sha256":"15ed8ce84cf487baf5081c08ad91632d511cc77748d9c01cbb767d2a86980b9b"},"schema_version":"1.0","source":{"id":"1903.09761","kind":"arxiv","version":1}},"canonical_sha256":"5ac95ac670b61e4f5eee76d84b4b542237968100ac598ab4a7a3425a647b4efa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ac95ac670b61e4f5eee76d84b4b542237968100ac598ab4a7a3425a647b4efa","first_computed_at":"2026-05-17T23:50:35.576445Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:50:35.576445Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UdqsV05VEzKYlgu9yac6NkdOH5Up2SWymyEaDb9DhShO3h25A4ePFPU6d93uRDe0TY2wgsZ3t5Mqd5nP19qYCQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:50:35.577225Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.09761","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29130f69a6ee05552591ba7bc7f3821f76110134eacf55f84b6592fc63e0444e","sha256:b708b4f01c628c911c534c59c138e49190f6653040ebd09cea4fd46fe04d9894"],"state_sha256":"e3a2157791c27a6f9ae1b069217e735dea89ac107bbf1aa54a74fae13e739112"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VeTSxw0NamYgdLwwawgayz6N5yNO2/1e42Z8bpCUQRntcq/jnf474OjrWcsI08sUqVTQi6rO8pjsA6JUuHkgAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T15:49:39.334550Z","bundle_sha256":"da569cdf75b42b90736f1d9c7aebed4b08febfca7bedf37e93981d2dd444f369"}}