{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:NIYCNQI7LATJGI67RLNFZG7NRK","short_pith_number":"pith:NIYCNQI7","canonical_record":{"source":{"id":"1809.04766","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-13T04:19:26Z","cross_cats_sorted":[],"title_canon_sha256":"7cc605516a37224eacc141bfd086541d8d7b96edcce172fa99c4d404929222e7","abstract_canon_sha256":"091fd341b7801fdf098ad5b0898a6870d5161e3687c83198fc66c2f4c08ea8fb"},"schema_version":"1.0"},"canonical_sha256":"6a3026c11f58269323df8ada5c9bed8a88a74fdb6d76618b811241dbd70f44f8","source":{"kind":"arxiv","id":"1809.04766","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.04766","created_at":"2026-05-17T23:52:33Z"},{"alias_kind":"arxiv_version","alias_value":"1809.04766v2","created_at":"2026-05-17T23:52:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.04766","created_at":"2026-05-17T23:52:33Z"},{"alias_kind":"pith_short_12","alias_value":"NIYCNQI7LATJ","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"NIYCNQI7LATJGI67","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"NIYCNQI7","created_at":"2026-05-18T12:32:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:NIYCNQI7LATJGI67RLNFZG7NRK","target":"record","payload":{"canonical_record":{"source":{"id":"1809.04766","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-13T04:19:26Z","cross_cats_sorted":[],"title_canon_sha256":"7cc605516a37224eacc141bfd086541d8d7b96edcce172fa99c4d404929222e7","abstract_canon_sha256":"091fd341b7801fdf098ad5b0898a6870d5161e3687c83198fc66c2f4c08ea8fb"},"schema_version":"1.0"},"canonical_sha256":"6a3026c11f58269323df8ada5c9bed8a88a74fdb6d76618b811241dbd70f44f8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:33.815428Z","signature_b64":"624wdlIzEBVxnobt4IryNiRsI2UE2WgOYVooxVH/EfNyNzLO+csoYuR+xRFNI35kRjhCz5oN8N+uuy2MhOvhBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a3026c11f58269323df8ada5c9bed8a88a74fdb6d76618b811241dbd70f44f8","last_reissued_at":"2026-05-17T23:52:33.815057Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:33.815057Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.04766","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:52:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dkD+DV1r0NHwtWWT5GEOoPkXkHaLaW9eNQ8Tfn2TQHjeTSyZnW0grIiUy+8V6heapnehu4o1K9O52kKdXuclAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T19:59:41.460898Z"},"content_sha256":"c0dd5fe5626c595f4d6258b57da6e6a6c1aa8330b4cfa3a2e8f76938fd32e8c5","schema_version":"1.0","event_id":"sha256:c0dd5fe5626c595f4d6258b57da6e6a6c1aa8330b4cfa3a2e8f76938fd32e8c5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:NIYCNQI7LATJGI67RLNFZG7NRK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrew Spek, Chunhua Shen, Ian Reid, Thanuja Dharmasiri, Tom Drummond, Vladimir Nekrasov","submitted_at":"2018-09-13T04:19:26Z","abstract_excerpt":"Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards. Here, we address three of its most prominent hurdles, namely, i) the adaptation of a single model to perform multiple tasks at once (in this work, we consider depth estimation and semantic segmentation crucial for acquiring geometric and semantic understanding of the scene), while ii) doing it in real-time, and iii) using asymmetric datasets with uneven numbers of annotations per each modality. To overcome the first two issues, we adapt a recently pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.04766","kind":"arxiv","version":2},"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":"2026-05-17T23:52:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9XHIjDRIrOfBO3LE4PaGWa615+3ms3RI97cQusJZPl+64vrU8O3eud5yF5IgqjBeRebyBJFhJdjIWxcmCQKgCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T19:59:41.461599Z"},"content_sha256":"988f564a5ffaf4e5d42a028dfd5856e3c91150e42ed7cf24bd26221914c2be63","schema_version":"1.0","event_id":"sha256:988f564a5ffaf4e5d42a028dfd5856e3c91150e42ed7cf24bd26221914c2be63"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NIYCNQI7LATJGI67RLNFZG7NRK/bundle.json","state_url":"https://pith.science/pith/NIYCNQI7LATJGI67RLNFZG7NRK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NIYCNQI7LATJGI67RLNFZG7NRK/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":"2026-05-28T19:59:41Z","links":{"resolver":"https://pith.science/pith/NIYCNQI7LATJGI67RLNFZG7NRK","bundle":"https://pith.science/pith/NIYCNQI7LATJGI67RLNFZG7NRK/bundle.json","state":"https://pith.science/pith/NIYCNQI7LATJGI67RLNFZG7NRK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NIYCNQI7LATJGI67RLNFZG7NRK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:NIYCNQI7LATJGI67RLNFZG7NRK","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":"091fd341b7801fdf098ad5b0898a6870d5161e3687c83198fc66c2f4c08ea8fb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-13T04:19:26Z","title_canon_sha256":"7cc605516a37224eacc141bfd086541d8d7b96edcce172fa99c4d404929222e7"},"schema_version":"1.0","source":{"id":"1809.04766","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.04766","created_at":"2026-05-17T23:52:33Z"},{"alias_kind":"arxiv_version","alias_value":"1809.04766v2","created_at":"2026-05-17T23:52:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.04766","created_at":"2026-05-17T23:52:33Z"},{"alias_kind":"pith_short_12","alias_value":"NIYCNQI7LATJ","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_16","alias_value":"NIYCNQI7LATJGI67","created_at":"2026-05-18T12:32:40Z"},{"alias_kind":"pith_short_8","alias_value":"NIYCNQI7","created_at":"2026-05-18T12:32:40Z"}],"graph_snapshots":[{"event_id":"sha256:988f564a5ffaf4e5d42a028dfd5856e3c91150e42ed7cf24bd26221914c2be63","target":"graph","created_at":"2026-05-17T23:52:33Z","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":"Deployment of deep learning models in robotics as sensory information extractors can be a daunting task to handle, even using generic GPU cards. Here, we address three of its most prominent hurdles, namely, i) the adaptation of a single model to perform multiple tasks at once (in this work, we consider depth estimation and semantic segmentation crucial for acquiring geometric and semantic understanding of the scene), while ii) doing it in real-time, and iii) using asymmetric datasets with uneven numbers of annotations per each modality. To overcome the first two issues, we adapt a recently pro","authors_text":"Andrew Spek, Chunhua Shen, Ian Reid, Thanuja Dharmasiri, Tom Drummond, Vladimir Nekrasov","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-13T04:19:26Z","title":"Real-Time Joint Semantic Segmentation and Depth Estimation Using Asymmetric Annotations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.04766","kind":"arxiv","version":2},"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:c0dd5fe5626c595f4d6258b57da6e6a6c1aa8330b4cfa3a2e8f76938fd32e8c5","target":"record","created_at":"2026-05-17T23:52:33Z","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":"091fd341b7801fdf098ad5b0898a6870d5161e3687c83198fc66c2f4c08ea8fb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-13T04:19:26Z","title_canon_sha256":"7cc605516a37224eacc141bfd086541d8d7b96edcce172fa99c4d404929222e7"},"schema_version":"1.0","source":{"id":"1809.04766","kind":"arxiv","version":2}},"canonical_sha256":"6a3026c11f58269323df8ada5c9bed8a88a74fdb6d76618b811241dbd70f44f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a3026c11f58269323df8ada5c9bed8a88a74fdb6d76618b811241dbd70f44f8","first_computed_at":"2026-05-17T23:52:33.815057Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:33.815057Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"624wdlIzEBVxnobt4IryNiRsI2UE2WgOYVooxVH/EfNyNzLO+csoYuR+xRFNI35kRjhCz5oN8N+uuy2MhOvhBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:33.815428Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.04766","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0dd5fe5626c595f4d6258b57da6e6a6c1aa8330b4cfa3a2e8f76938fd32e8c5","sha256:988f564a5ffaf4e5d42a028dfd5856e3c91150e42ed7cf24bd26221914c2be63"],"state_sha256":"4ee2cd52071ba40d8822c0ed0cbb023c7f9b1aaf10b1cb4f2a3f49d215f97fec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"75OKPg+09LhKM+yRnSTlSZzj6csrpoEvlw8MLPpgQ5EETIS1ARzCcEoXKzAxu7U9ZsD+m5kH87XlSYuQ+BkqBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T19:59:41.465625Z","bundle_sha256":"6e4a3456d89298af11b149ce942e515cd5b939007467fd24937182639482392f"}}