{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:LFMVTAPDZ6NQDMYXU2U5HFDK7I","short_pith_number":"pith:LFMVTAPD","canonical_record":{"source":{"id":"2209.14829","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-29T14:45:47Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"11729b9679d7575bf483ecb4fa0c920187e46704d2577073c426677676a7e2a4","abstract_canon_sha256":"f752ca2fbd6fb4273644796bacb5b9172f85c9290c02f357c20209bfb7d3020f"},"schema_version":"1.0"},"canonical_sha256":"59595981e3cf9b01b317a6a9d3946afa2c6016450848ef3bd15773d1cc47e2e1","source":{"kind":"arxiv","id":"2209.14829","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.14829","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"arxiv_version","alias_value":"2209.14829v1","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.14829","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"pith_short_12","alias_value":"LFMVTAPDZ6NQ","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"pith_short_16","alias_value":"LFMVTAPDZ6NQDMYX","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"pith_short_8","alias_value":"LFMVTAPD","created_at":"2026-07-05T05:02:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:LFMVTAPDZ6NQDMYXU2U5HFDK7I","target":"record","payload":{"canonical_record":{"source":{"id":"2209.14829","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-29T14:45:47Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"11729b9679d7575bf483ecb4fa0c920187e46704d2577073c426677676a7e2a4","abstract_canon_sha256":"f752ca2fbd6fb4273644796bacb5b9172f85c9290c02f357c20209bfb7d3020f"},"schema_version":"1.0"},"canonical_sha256":"59595981e3cf9b01b317a6a9d3946afa2c6016450848ef3bd15773d1cc47e2e1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:02:06.034450Z","signature_b64":"ICVs+5RLQ1SFf3R2mm+MI94KXz0S62EEeQpEDs2Y9SUJm1AcP0s5Bs3Uer3brJo8tFgVY/Ois/IjBYWDpjdoCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59595981e3cf9b01b317a6a9d3946afa2c6016450848ef3bd15773d1cc47e2e1","last_reissued_at":"2026-07-05T05:02:06.034037Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:02:06.034037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2209.14829","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":"2026-07-05T05:02:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qBkrKXkFVkhi4hcRmE1u3GS4BIYr1svrP6t0a25bXvyygJD8Blveadjg/eYXwKtR76E9oqN35+ukbNmCGM1pDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T07:55:27.775474Z"},"content_sha256":"3e709e7d628ab0cb4db384defd760054fae033f683fbb89184626ed743efe114","schema_version":"1.0","event_id":"sha256:3e709e7d628ab0cb4db384defd760054fae033f683fbb89184626ed743efe114"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:LFMVTAPDZ6NQDMYXU2U5HFDK7I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Lightweight Monocular Depth Estimation with an Edge Guided Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Hussein A. Abbass, Junyu Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Xingshuai Dong","submitted_at":"2022-09-29T14:45:47Z","abstract_excerpt":"Monocular depth estimation is an important task that can be applied to many robotic applications. Existing methods focus on improving depth estimation accuracy via training increasingly deeper and wider networks, however these suffer from large computational complexity. Recent studies found that edge information are important cues for convolutional neural networks (CNNs) to estimate depth. Inspired by the above observations, we present a novel lightweight Edge Guided Depth Estimation Network (EGD-Net) in this study. In particular, we start out with a lightweight encoder-decoder architecture an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.14829","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2209.14829/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":"2026-07-05T05:02:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EgeBNqHlFzDKx7uJjK0g0qChOu3H8GuVFwthAAtT51oVMeKf8VhPbbeevqvhkaqd0wO1gIrkmlsq7rVvtfwZDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T07:55:27.776319Z"},"content_sha256":"ba7b6cfaf0bcebc9ba69b1f303630791c8a9b8398741e50a827e594b4c4f57ef","schema_version":"1.0","event_id":"sha256:ba7b6cfaf0bcebc9ba69b1f303630791c8a9b8398741e50a827e594b4c4f57ef"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LFMVTAPDZ6NQDMYXU2U5HFDK7I/bundle.json","state_url":"https://pith.science/pith/LFMVTAPDZ6NQDMYXU2U5HFDK7I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LFMVTAPDZ6NQDMYXU2U5HFDK7I/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":"2026-08-19T07:55:27Z","links":{"resolver":"https://pith.science/pith/LFMVTAPDZ6NQDMYXU2U5HFDK7I","bundle":"https://pith.science/pith/LFMVTAPDZ6NQDMYXU2U5HFDK7I/bundle.json","state":"https://pith.science/pith/LFMVTAPDZ6NQDMYXU2U5HFDK7I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LFMVTAPDZ6NQDMYXU2U5HFDK7I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LFMVTAPDZ6NQDMYXU2U5HFDK7I","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":"f752ca2fbd6fb4273644796bacb5b9172f85c9290c02f357c20209bfb7d3020f","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-29T14:45:47Z","title_canon_sha256":"11729b9679d7575bf483ecb4fa0c920187e46704d2577073c426677676a7e2a4"},"schema_version":"1.0","source":{"id":"2209.14829","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.14829","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"arxiv_version","alias_value":"2209.14829v1","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.14829","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"pith_short_12","alias_value":"LFMVTAPDZ6NQ","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"pith_short_16","alias_value":"LFMVTAPDZ6NQDMYX","created_at":"2026-07-05T05:02:06Z"},{"alias_kind":"pith_short_8","alias_value":"LFMVTAPD","created_at":"2026-07-05T05:02:06Z"}],"graph_snapshots":[{"event_id":"sha256:ba7b6cfaf0bcebc9ba69b1f303630791c8a9b8398741e50a827e594b4c4f57ef","target":"graph","created_at":"2026-07-05T05:02:06Z","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/2209.14829/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Monocular depth estimation is an important task that can be applied to many robotic applications. Existing methods focus on improving depth estimation accuracy via training increasingly deeper and wider networks, however these suffer from large computational complexity. Recent studies found that edge information are important cues for convolutional neural networks (CNNs) to estimate depth. Inspired by the above observations, we present a novel lightweight Edge Guided Depth Estimation Network (EGD-Net) in this study. In particular, we start out with a lightweight encoder-decoder architecture an","authors_text":"Hussein A. Abbass, Junyu Dong, Matthew A. Garratt, Sreenatha G. Anavatti, Xingshuai Dong","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-29T14:45:47Z","title":"Lightweight Monocular Depth Estimation with an Edge Guided Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.14829","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":"sha256:3e709e7d628ab0cb4db384defd760054fae033f683fbb89184626ed743efe114","target":"record","created_at":"2026-07-05T05:02:06Z","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":"f752ca2fbd6fb4273644796bacb5b9172f85c9290c02f357c20209bfb7d3020f","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-29T14:45:47Z","title_canon_sha256":"11729b9679d7575bf483ecb4fa0c920187e46704d2577073c426677676a7e2a4"},"schema_version":"1.0","source":{"id":"2209.14829","kind":"arxiv","version":1}},"canonical_sha256":"59595981e3cf9b01b317a6a9d3946afa2c6016450848ef3bd15773d1cc47e2e1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59595981e3cf9b01b317a6a9d3946afa2c6016450848ef3bd15773d1cc47e2e1","first_computed_at":"2026-07-05T05:02:06.034037Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:02:06.034037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ICVs+5RLQ1SFf3R2mm+MI94KXz0S62EEeQpEDs2Y9SUJm1AcP0s5Bs3Uer3brJo8tFgVY/Ois/IjBYWDpjdoCA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:02:06.034450Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.14829","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e709e7d628ab0cb4db384defd760054fae033f683fbb89184626ed743efe114","sha256:ba7b6cfaf0bcebc9ba69b1f303630791c8a9b8398741e50a827e594b4c4f57ef"],"state_sha256":"fa01005553d2818ed1b3cdf20f16dd52b5134ca23f0cad1febf7a27b4f3b7834"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SIOKytjnNvw7yVlDwkZn7kuOFuxv2ZQecHfSuZHSKQnscG9UGSVHqYudx1JJR89f7TzqZBOt4MkM73jhaywdAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T07:55:27.782882Z","bundle_sha256":"9977c00be8940c5985c83316d0a7e73e982ea1794a0fe4df87dd2afa336b368d"}}