{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:UBYSBVC4AWOXX5GQQXG2UMETIA","short_pith_number":"pith:UBYSBVC4","canonical_record":{"source":{"id":"1604.07480","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-25T23:58:00Z","cross_cats_sorted":[],"title_canon_sha256":"6c4c01adff975752c9d08e8728f513765a9da91dcdae0e8cf636cb483d3eb746","abstract_canon_sha256":"740deaf4f13c1f72c692a46f76e34cb48bbcdcce9b135d7825128a95c32558ea"},"schema_version":"1.0"},"canonical_sha256":"a07120d45c059d7bf4d085cdaa30934037f7d1f108a67955712ae42af097540a","source":{"kind":"arxiv","id":"1604.07480","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.07480","created_at":"2026-05-18T01:04:20Z"},{"alias_kind":"arxiv_version","alias_value":"1604.07480v3","created_at":"2026-05-18T01:04:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.07480","created_at":"2026-05-18T01:04:20Z"},{"alias_kind":"pith_short_12","alias_value":"UBYSBVC4AWOX","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_16","alias_value":"UBYSBVC4AWOXX5GQ","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_8","alias_value":"UBYSBVC4","created_at":"2026-05-18T12:30:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:UBYSBVC4AWOXX5GQQXG2UMETIA","target":"record","payload":{"canonical_record":{"source":{"id":"1604.07480","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-25T23:58:00Z","cross_cats_sorted":[],"title_canon_sha256":"6c4c01adff975752c9d08e8728f513765a9da91dcdae0e8cf636cb483d3eb746","abstract_canon_sha256":"740deaf4f13c1f72c692a46f76e34cb48bbcdcce9b135d7825128a95c32558ea"},"schema_version":"1.0"},"canonical_sha256":"a07120d45c059d7bf4d085cdaa30934037f7d1f108a67955712ae42af097540a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:20.774198Z","signature_b64":"5v4W2CfZkMHY3Lv1lCq8n2vu6GpsBlZ4lf7jJ5zCco2EHlx+FkmZg7o5ws4L+yGlFdW/LGV4PC1ou8MOl3UJBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a07120d45c059d7bf4d085cdaa30934037f7d1f108a67955712ae42af097540a","last_reissued_at":"2026-05-18T01:04:20.773632Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:20.773632Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1604.07480","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:04:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tTr1qlku0IhlNfnw2efHKYxJrB1tbU6JoMbPFp9mU/rlYH/j1NOfiXg+CjYKExuTudXgps1+W35IC6D4qxRQDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T20:27:01.124309Z"},"content_sha256":"8d0ba398c91d8d1dc2dee67988577c0b4e1cdeae9854e0dfb79241437346727e","schema_version":"1.0","event_id":"sha256:8d0ba398c91d8d1dc2dee67988577c0b4e1cdeae9854e0dfb79241437346727e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:UBYSBVC4AWOXX5GQQXG2UMETIA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Arsalan Mousavian, Hamed Pirsiavash, Jana Kosecka","submitted_at":"2016-04-25T23:58:00Z","abstract_excerpt":"Multi-scale deep CNNs have been used successfully for problems mapping each pixel to a label, such as depth estimation and semantic segmentation. It has also been shown that such architectures are reusable and can be used for multiple tasks. These networks are typically trained independently for each task by varying the output layer(s) and training objective. In this work we present a new model for simultaneous depth estimation and semantic segmentation from a single RGB image. Our approach demonstrates the feasibility of training parts of the model for each task and then fine tuning the full,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.07480","kind":"arxiv","version":3},"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":"2026-05-18T01:04:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xCBfoc9H2vx03SCqe2UKf7SxOf5soNBdYwj7RmjQgLtMZOXHTqch9hxRORP9jdPKk4+aHNHFEZBPXRVhNSIwAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T20:27:01.125169Z"},"content_sha256":"92154aa2ad3404b237071878aae81f26d0ecce4e542919c17b2a2872006bb9e2","schema_version":"1.0","event_id":"sha256:92154aa2ad3404b237071878aae81f26d0ecce4e542919c17b2a2872006bb9e2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UBYSBVC4AWOXX5GQQXG2UMETIA/bundle.json","state_url":"https://pith.science/pith/UBYSBVC4AWOXX5GQQXG2UMETIA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UBYSBVC4AWOXX5GQQXG2UMETIA/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":"2026-05-30T20:27:01Z","links":{"resolver":"https://pith.science/pith/UBYSBVC4AWOXX5GQQXG2UMETIA","bundle":"https://pith.science/pith/UBYSBVC4AWOXX5GQQXG2UMETIA/bundle.json","state":"https://pith.science/pith/UBYSBVC4AWOXX5GQQXG2UMETIA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UBYSBVC4AWOXX5GQQXG2UMETIA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:UBYSBVC4AWOXX5GQQXG2UMETIA","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":"740deaf4f13c1f72c692a46f76e34cb48bbcdcce9b135d7825128a95c32558ea","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-25T23:58:00Z","title_canon_sha256":"6c4c01adff975752c9d08e8728f513765a9da91dcdae0e8cf636cb483d3eb746"},"schema_version":"1.0","source":{"id":"1604.07480","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.07480","created_at":"2026-05-18T01:04:20Z"},{"alias_kind":"arxiv_version","alias_value":"1604.07480v3","created_at":"2026-05-18T01:04:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.07480","created_at":"2026-05-18T01:04:20Z"},{"alias_kind":"pith_short_12","alias_value":"UBYSBVC4AWOX","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_16","alias_value":"UBYSBVC4AWOXX5GQ","created_at":"2026-05-18T12:30:46Z"},{"alias_kind":"pith_short_8","alias_value":"UBYSBVC4","created_at":"2026-05-18T12:30:46Z"}],"graph_snapshots":[{"event_id":"sha256:92154aa2ad3404b237071878aae81f26d0ecce4e542919c17b2a2872006bb9e2","target":"graph","created_at":"2026-05-18T01:04:20Z","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":"Multi-scale deep CNNs have been used successfully for problems mapping each pixel to a label, such as depth estimation and semantic segmentation. It has also been shown that such architectures are reusable and can be used for multiple tasks. These networks are typically trained independently for each task by varying the output layer(s) and training objective. In this work we present a new model for simultaneous depth estimation and semantic segmentation from a single RGB image. Our approach demonstrates the feasibility of training parts of the model for each task and then fine tuning the full,","authors_text":"Arsalan Mousavian, Hamed Pirsiavash, Jana Kosecka","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-25T23:58:00Z","title":"Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.07480","kind":"arxiv","version":3},"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":"sha256:8d0ba398c91d8d1dc2dee67988577c0b4e1cdeae9854e0dfb79241437346727e","target":"record","created_at":"2026-05-18T01:04:20Z","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":"740deaf4f13c1f72c692a46f76e34cb48bbcdcce9b135d7825128a95c32558ea","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-25T23:58:00Z","title_canon_sha256":"6c4c01adff975752c9d08e8728f513765a9da91dcdae0e8cf636cb483d3eb746"},"schema_version":"1.0","source":{"id":"1604.07480","kind":"arxiv","version":3}},"canonical_sha256":"a07120d45c059d7bf4d085cdaa30934037f7d1f108a67955712ae42af097540a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a07120d45c059d7bf4d085cdaa30934037f7d1f108a67955712ae42af097540a","first_computed_at":"2026-05-18T01:04:20.773632Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:04:20.773632Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5v4W2CfZkMHY3Lv1lCq8n2vu6GpsBlZ4lf7jJ5zCco2EHlx+FkmZg7o5ws4L+yGlFdW/LGV4PC1ou8MOl3UJBg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:04:20.774198Z","signed_message":"canonical_sha256_bytes"},"source_id":"1604.07480","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d0ba398c91d8d1dc2dee67988577c0b4e1cdeae9854e0dfb79241437346727e","sha256:92154aa2ad3404b237071878aae81f26d0ecce4e542919c17b2a2872006bb9e2"],"state_sha256":"b5b156272a342f7c78d888050cf1e1e803b0c12593a174b3b1bb9923019c0aab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q4TeMZUzsSYpjG2IaMNTSVehI7GYkDuxWn4m1u9WXIAAfkZ8KiLdYUF9P1/r68GFUnUnoeUY5RsE0eWAeNkHBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T20:27:01.129885Z","bundle_sha256":"3be0a8fe928d5096a0560914d92ee7be800a9790facc98b80f4747b24b5f395c"}}