{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:TQV3NHLMO5GYZMANYLY4JUOSMC","short_pith_number":"pith:TQV3NHLM","canonical_record":{"source":{"id":"1709.01956","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-06T18:19:10Z","cross_cats_sorted":[],"title_canon_sha256":"37835f76af32b095d13016d33e22627d55606cad9cfaeba7315c1142753f1423","abstract_canon_sha256":"6f6f0a80b3ddd31c35654c0c4a351a7951fccf3b6e3d359a9c047bca8b823666"},"schema_version":"1.0"},"canonical_sha256":"9c2bb69d6c774d8cb00dc2f1c4d1d260b6ef990e68f837c688481ae6943f699d","source":{"kind":"arxiv","id":"1709.01956","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.01956","created_at":"2026-05-18T00:35:50Z"},{"alias_kind":"arxiv_version","alias_value":"1709.01956v1","created_at":"2026-05-18T00:35:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.01956","created_at":"2026-05-18T00:35:50Z"},{"alias_kind":"pith_short_12","alias_value":"TQV3NHLMO5GY","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TQV3NHLMO5GYZMAN","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TQV3NHLM","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:TQV3NHLMO5GYZMANYLY4JUOSMC","target":"record","payload":{"canonical_record":{"source":{"id":"1709.01956","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-06T18:19:10Z","cross_cats_sorted":[],"title_canon_sha256":"37835f76af32b095d13016d33e22627d55606cad9cfaeba7315c1142753f1423","abstract_canon_sha256":"6f6f0a80b3ddd31c35654c0c4a351a7951fccf3b6e3d359a9c047bca8b823666"},"schema_version":"1.0"},"canonical_sha256":"9c2bb69d6c774d8cb00dc2f1c4d1d260b6ef990e68f837c688481ae6943f699d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:50.727438Z","signature_b64":"M3r27uB5ZY5rCC9xXDA5cEb6hxO2Qo0C+BgkJL2nLdN27RVhAhFOkAEHwg6uzoVmnkHSjUbvHtoGkkuXSC83DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c2bb69d6c774d8cb00dc2f1c4d1d260b6ef990e68f837c688481ae6943f699d","last_reissued_at":"2026-05-18T00:35:50.726594Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:50.726594Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1709.01956","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":"2026-05-18T00:35:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WUKgADnq9QpuEfGShQRlf8X/CBNmu9tUvDLNzQj1b7nxhzpNu8YpeJOomlbrSeud0v2IqNAz8FlgtICX4Bm6Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T22:05:48.141507Z"},"content_sha256":"f3fa7cf484614305e581e07dd7b9e9098985922a0cef73b7f354e46f7fb4f941","schema_version":"1.0","event_id":"sha256:f3fa7cf484614305e581e07dd7b9e9098985922a0cef73b7f354e46f7fb4f941"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:TQV3NHLMO5GYZMANYLY4JUOSMC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Dilation Factors for Semantic Segmentation of Street Scenes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bernt Schiele, Margret Keuper, Mario Fritz, Yang He","submitted_at":"2017-09-06T18:19:10Z","abstract_excerpt":"Contextual information is crucial for semantic segmentation. However, finding the optimal trade-off between keeping desired fine details and at the same time providing sufficiently large receptive fields is non trivial. This is even more so, when objects or classes present in an image significantly vary in size. Dilated convolutions have proven valuable for semantic segmentation, because they allow to increase the size of the receptive field without sacrificing image resolution. However, in current state-of-the-art methods, dilation parameters are hand-tuned and fixed. In this paper, we presen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.01956","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":"2026-05-18T00:35:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4PUAHjeaFjKbPZY5aS1oSxndLNNqWjVkax4ThcNYsK3SpWiNs+7k9O9DXauKV6gqVBF9HzxxmKPOBXTqRCwVAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T22:05:48.142397Z"},"content_sha256":"107b6e5a5c83062c64d429de83fe4628aefd351e456f68d15f357249e56bc927","schema_version":"1.0","event_id":"sha256:107b6e5a5c83062c64d429de83fe4628aefd351e456f68d15f357249e56bc927"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TQV3NHLMO5GYZMANYLY4JUOSMC/bundle.json","state_url":"https://pith.science/pith/TQV3NHLMO5GYZMANYLY4JUOSMC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TQV3NHLMO5GYZMANYLY4JUOSMC/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":"2026-06-06T22:05:48Z","links":{"resolver":"https://pith.science/pith/TQV3NHLMO5GYZMANYLY4JUOSMC","bundle":"https://pith.science/pith/TQV3NHLMO5GYZMANYLY4JUOSMC/bundle.json","state":"https://pith.science/pith/TQV3NHLMO5GYZMANYLY4JUOSMC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TQV3NHLMO5GYZMANYLY4JUOSMC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:TQV3NHLMO5GYZMANYLY4JUOSMC","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":"6f6f0a80b3ddd31c35654c0c4a351a7951fccf3b6e3d359a9c047bca8b823666","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-06T18:19:10Z","title_canon_sha256":"37835f76af32b095d13016d33e22627d55606cad9cfaeba7315c1142753f1423"},"schema_version":"1.0","source":{"id":"1709.01956","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.01956","created_at":"2026-05-18T00:35:50Z"},{"alias_kind":"arxiv_version","alias_value":"1709.01956v1","created_at":"2026-05-18T00:35:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.01956","created_at":"2026-05-18T00:35:50Z"},{"alias_kind":"pith_short_12","alias_value":"TQV3NHLMO5GY","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TQV3NHLMO5GYZMAN","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TQV3NHLM","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:107b6e5a5c83062c64d429de83fe4628aefd351e456f68d15f357249e56bc927","target":"graph","created_at":"2026-05-18T00:35:50Z","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":"Contextual information is crucial for semantic segmentation. However, finding the optimal trade-off between keeping desired fine details and at the same time providing sufficiently large receptive fields is non trivial. This is even more so, when objects or classes present in an image significantly vary in size. Dilated convolutions have proven valuable for semantic segmentation, because they allow to increase the size of the receptive field without sacrificing image resolution. However, in current state-of-the-art methods, dilation parameters are hand-tuned and fixed. In this paper, we presen","authors_text":"Bernt Schiele, Margret Keuper, Mario Fritz, Yang He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-06T18:19:10Z","title":"Learning Dilation Factors for Semantic Segmentation of Street Scenes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.01956","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:f3fa7cf484614305e581e07dd7b9e9098985922a0cef73b7f354e46f7fb4f941","target":"record","created_at":"2026-05-18T00:35:50Z","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":"6f6f0a80b3ddd31c35654c0c4a351a7951fccf3b6e3d359a9c047bca8b823666","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-06T18:19:10Z","title_canon_sha256":"37835f76af32b095d13016d33e22627d55606cad9cfaeba7315c1142753f1423"},"schema_version":"1.0","source":{"id":"1709.01956","kind":"arxiv","version":1}},"canonical_sha256":"9c2bb69d6c774d8cb00dc2f1c4d1d260b6ef990e68f837c688481ae6943f699d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c2bb69d6c774d8cb00dc2f1c4d1d260b6ef990e68f837c688481ae6943f699d","first_computed_at":"2026-05-18T00:35:50.726594Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:35:50.726594Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"M3r27uB5ZY5rCC9xXDA5cEb6hxO2Qo0C+BgkJL2nLdN27RVhAhFOkAEHwg6uzoVmnkHSjUbvHtoGkkuXSC83DQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:35:50.727438Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.01956","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f3fa7cf484614305e581e07dd7b9e9098985922a0cef73b7f354e46f7fb4f941","sha256:107b6e5a5c83062c64d429de83fe4628aefd351e456f68d15f357249e56bc927"],"state_sha256":"97b7c987ad04779397fc820cba06a766c6b94259f8f0eabd32dd575042b29013"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mUQhDWMUjWWygo32nIl5wBjxmQlnuqzfOeQHV5iZlvxm5lC4HVD1yMCJOA98MqLRgThXQDmWY5zicm+OvE8JAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T22:05:48.146231Z","bundle_sha256":"3d44f36fd80febe6abdd6fdcf1e6d5dab232878b88eaef8e12afd31474410ee2"}}