{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:TCFSNQFSLKZJE66ZMNXH77FQUA","short_pith_number":"pith:TCFSNQFS","canonical_record":{"source":{"id":"2005.04437","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-05-09T13:05:06Z","cross_cats_sorted":[],"title_canon_sha256":"f5c85c3935607685c4c41214b376848fd66c178f0bd7d4bb7890599efde07ec9","abstract_canon_sha256":"65cec313549ece4eb8134012c7cc3926edc480396544968615118df23f9e9c60"},"schema_version":"1.0"},"canonical_sha256":"988b26c0b25ab2927bd9636e7ffcb0a03f4d2a3dcea18d36105c2d2a3d1ac587","source":{"kind":"arxiv","id":"2005.04437","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.04437","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"arxiv_version","alias_value":"2005.04437v5","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.04437","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"pith_short_12","alias_value":"TCFSNQFSLKZJ","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"pith_short_16","alias_value":"TCFSNQFSLKZJE66Z","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"pith_short_8","alias_value":"TCFSNQFS","created_at":"2026-07-05T01:27:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:TCFSNQFSLKZJE66ZMNXH77FQUA","target":"record","payload":{"canonical_record":{"source":{"id":"2005.04437","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-05-09T13:05:06Z","cross_cats_sorted":[],"title_canon_sha256":"f5c85c3935607685c4c41214b376848fd66c178f0bd7d4bb7890599efde07ec9","abstract_canon_sha256":"65cec313549ece4eb8134012c7cc3926edc480396544968615118df23f9e9c60"},"schema_version":"1.0"},"canonical_sha256":"988b26c0b25ab2927bd9636e7ffcb0a03f4d2a3dcea18d36105c2d2a3d1ac587","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:27:03.423802Z","signature_b64":"rnNzBpalXxlBW8HRU9MRc3GkJfnwG9N5g+ahmzJY9SchZzqb0ntG/dkM31N+JtG+kCpS1ZIzWJVZ1bup/lgeBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"988b26c0b25ab2927bd9636e7ffcb0a03f4d2a3dcea18d36105c2d2a3d1ac587","last_reissued_at":"2026-07-05T01:27:03.423395Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:27:03.423395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2005.04437","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:27:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gfBAeO2BQA7vqCl90jqih6CIA3mjlt7tOLmO2CNoCNhvPaNnKuH8AprlOOnAfZHvqCX259nUFgKQSnlod8ZbAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:55:47.262967Z"},"content_sha256":"1974a6a2960ee9e95501aa8740c9e4fa38048a315dce0e7a99dfec51fa6c6eca","schema_version":"1.0","event_id":"sha256:1974a6a2960ee9e95501aa8740c9e4fa38048a315dce0e7a99dfec51fa6c6eca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:TCFSNQFSLKZJE66ZMNXH77FQUA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding Dynamic Scenes using Graph Convolution Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anoop Namboodiri, Balaraman Ravindran, K Madhava Krishna, Mahtab Sandhu, Priyesh Vijayan, Sravan Mylavarapu","submitted_at":"2020-05-09T13:05:06Z","abstract_excerpt":"We present a novel Multi-Relational Graph Convolutional Network (MRGCN) based framework to model on-road vehicle behaviors from a sequence of temporally ordered frames as grabbed by a moving monocular camera. The input to MRGCN is a multi-relational graph where the graph's nodes represent the active and passive agents/objects in the scene, and the bidirectional edges that connect every pair of nodes are encodings of their Spatio-temporal relations. We show that this proposed explicit encoding and usage of an intermediate spatio-temporal interaction graph to be well suited for our tasks over le"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.04437","kind":"arxiv","version":5},"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/2005.04437/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:27:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QPbXmtR8QiIlzr9E5E+Kt9yFLoo0pymLuoPp3JRxvV7dmEdNA0xblTjPQ6cI6uyJFh2e3lzn16VYks0uoLUqDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:55:47.263340Z"},"content_sha256":"11ce4cfb7329c399c6b490eddea807d2bb873a8c2a62187419a953f281e369b8","schema_version":"1.0","event_id":"sha256:11ce4cfb7329c399c6b490eddea807d2bb873a8c2a62187419a953f281e369b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TCFSNQFSLKZJE66ZMNXH77FQUA/bundle.json","state_url":"https://pith.science/pith/TCFSNQFSLKZJE66ZMNXH77FQUA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TCFSNQFSLKZJE66ZMNXH77FQUA/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":"2026-07-07T11:55:47Z","links":{"resolver":"https://pith.science/pith/TCFSNQFSLKZJE66ZMNXH77FQUA","bundle":"https://pith.science/pith/TCFSNQFSLKZJE66ZMNXH77FQUA/bundle.json","state":"https://pith.science/pith/TCFSNQFSLKZJE66ZMNXH77FQUA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TCFSNQFSLKZJE66ZMNXH77FQUA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:TCFSNQFSLKZJE66ZMNXH77FQUA","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":"65cec313549ece4eb8134012c7cc3926edc480396544968615118df23f9e9c60","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-05-09T13:05:06Z","title_canon_sha256":"f5c85c3935607685c4c41214b376848fd66c178f0bd7d4bb7890599efde07ec9"},"schema_version":"1.0","source":{"id":"2005.04437","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.04437","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"arxiv_version","alias_value":"2005.04437v5","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.04437","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"pith_short_12","alias_value":"TCFSNQFSLKZJ","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"pith_short_16","alias_value":"TCFSNQFSLKZJE66Z","created_at":"2026-07-05T01:27:03Z"},{"alias_kind":"pith_short_8","alias_value":"TCFSNQFS","created_at":"2026-07-05T01:27:03Z"}],"graph_snapshots":[{"event_id":"sha256:11ce4cfb7329c399c6b490eddea807d2bb873a8c2a62187419a953f281e369b8","target":"graph","created_at":"2026-07-05T01:27:03Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2005.04437/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a novel Multi-Relational Graph Convolutional Network (MRGCN) based framework to model on-road vehicle behaviors from a sequence of temporally ordered frames as grabbed by a moving monocular camera. The input to MRGCN is a multi-relational graph where the graph's nodes represent the active and passive agents/objects in the scene, and the bidirectional edges that connect every pair of nodes are encodings of their Spatio-temporal relations. We show that this proposed explicit encoding and usage of an intermediate spatio-temporal interaction graph to be well suited for our tasks over le","authors_text":"Anoop Namboodiri, Balaraman Ravindran, K Madhava Krishna, Mahtab Sandhu, Priyesh Vijayan, Sravan Mylavarapu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-05-09T13:05:06Z","title":"Understanding Dynamic Scenes using Graph Convolution Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.04437","kind":"arxiv","version":5},"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":"sha256:1974a6a2960ee9e95501aa8740c9e4fa38048a315dce0e7a99dfec51fa6c6eca","target":"record","created_at":"2026-07-05T01:27:03Z","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":"65cec313549ece4eb8134012c7cc3926edc480396544968615118df23f9e9c60","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-05-09T13:05:06Z","title_canon_sha256":"f5c85c3935607685c4c41214b376848fd66c178f0bd7d4bb7890599efde07ec9"},"schema_version":"1.0","source":{"id":"2005.04437","kind":"arxiv","version":5}},"canonical_sha256":"988b26c0b25ab2927bd9636e7ffcb0a03f4d2a3dcea18d36105c2d2a3d1ac587","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"988b26c0b25ab2927bd9636e7ffcb0a03f4d2a3dcea18d36105c2d2a3d1ac587","first_computed_at":"2026-07-05T01:27:03.423395Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:27:03.423395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rnNzBpalXxlBW8HRU9MRc3GkJfnwG9N5g+ahmzJY9SchZzqb0ntG/dkM31N+JtG+kCpS1ZIzWJVZ1bup/lgeBg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:27:03.423802Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.04437","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1974a6a2960ee9e95501aa8740c9e4fa38048a315dce0e7a99dfec51fa6c6eca","sha256:11ce4cfb7329c399c6b490eddea807d2bb873a8c2a62187419a953f281e369b8"],"state_sha256":"8e6e13f9e10006cd24fda1f3787d6c42bbf16f550fd6e34138405d416b6184f9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"77TmbULS2VbDMjNh3qY0BK5nz5iQKXaJ2kfz5XxmvguQHuPg4k/rvfE13IPtSGZjT9ZFebcmZaNZnFi4s7QRCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T11:55:47.265289Z","bundle_sha256":"cbe4e7ab819042ab443f43f3e77d0aeb591e38c8192a359d2177876baa713313"}}