{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:GP4JKTEO6X5EUS67RSTV5UXA34","short_pith_number":"pith:GP4JKTEO","canonical_record":{"source":{"id":"1802.10367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T11:27:41Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"e16a69044e72ccfde4e8c9e751767eb3c97fe26ed802997363e14b83356d36bc","abstract_canon_sha256":"915ef67e9dd8ef81729a6a155a2ac40413400b8a4c3559767716300df3e8600a"},"schema_version":"1.0"},"canonical_sha256":"33f8954c8ef5fa4a4bdf8ca75ed2e0df118131f7fb7de2306d7d504ce4855b14","source":{"kind":"arxiv","id":"1802.10367","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10367","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10367v1","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10367","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"pith_short_12","alias_value":"GP4JKTEO6X5E","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GP4JKTEO6X5EUS67","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GP4JKTEO","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:GP4JKTEO6X5EUS67RSTV5UXA34","target":"record","payload":{"canonical_record":{"source":{"id":"1802.10367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T11:27:41Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"e16a69044e72ccfde4e8c9e751767eb3c97fe26ed802997363e14b83356d36bc","abstract_canon_sha256":"915ef67e9dd8ef81729a6a155a2ac40413400b8a4c3559767716300df3e8600a"},"schema_version":"1.0"},"canonical_sha256":"33f8954c8ef5fa4a4bdf8ca75ed2e0df118131f7fb7de2306d7d504ce4855b14","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:22:17.339142Z","signature_b64":"9lC2k22zdEDBSZo+rxb/ReBJtDPAotd15YAA0EZitGFLGaQWliqpxYgJpzrnxJBeEj7zRy+GImUj1Mda/xR+Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"33f8954c8ef5fa4a4bdf8ca75ed2e0df118131f7fb7de2306d7d504ce4855b14","last_reissued_at":"2026-05-18T00:22:17.338498Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:22:17.338498Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.10367","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":"2026-05-18T00:22:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1wJbr7WMgz3rghv1dieOemRErAtzyvz8/lmIKXjUJk1IJE/NnPXiVwocqS1hEjSfYUYlNN4MSQ4f7Vd9YqxnAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T17:36:30.554817Z"},"content_sha256":"cde9f16342b17dc22fe5eb421684926d2b1c59fbf1507442d1f16ab03fea7270","schema_version":"1.0","event_id":"sha256:cde9f16342b17dc22fe5eb421684926d2b1c59fbf1507442d1f16ab03fea7270"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:GP4JKTEO6X5EUS67RSTV5UXA34","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Ian Reid, Ming Cai, Thanh-Toan Do, Trung Pham","submitted_at":"2018-02-28T11:27:41Z","abstract_excerpt":"Detecting objects and their 6D poses from only RGB images is an important task for many robotic applications. While deep learning methods have made significant progress in visual object detection and segmentation, the object pose estimation task is still challenging. In this paper, we introduce an end-toend deep learning framework, named Deep-6DPose, that jointly detects, segments, and most importantly recovers 6D poses of object instances from a single RGB image. In particular, we extend the recent state-of-the-art instance segmentation network Mask R-CNN with a novel pose estimation branch t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10367","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":"2026-05-18T00:22:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wPG1pELossw5SqzMRQKodxqiqlO1Hv2TlSC8Ojx2gNsWdfLRnwoUPEjwG5GL5zivcJ688IUQ0VNfMTuN/RPSCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T17:36:30.555497Z"},"content_sha256":"635f93c78f9c4add9997cb976ee2760d0aba8f106dc28878bacc30ea0f4724bc","schema_version":"1.0","event_id":"sha256:635f93c78f9c4add9997cb976ee2760d0aba8f106dc28878bacc30ea0f4724bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GP4JKTEO6X5EUS67RSTV5UXA34/bundle.json","state_url":"https://pith.science/pith/GP4JKTEO6X5EUS67RSTV5UXA34/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GP4JKTEO6X5EUS67RSTV5UXA34/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":"2026-05-27T17:36:30Z","links":{"resolver":"https://pith.science/pith/GP4JKTEO6X5EUS67RSTV5UXA34","bundle":"https://pith.science/pith/GP4JKTEO6X5EUS67RSTV5UXA34/bundle.json","state":"https://pith.science/pith/GP4JKTEO6X5EUS67RSTV5UXA34/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GP4JKTEO6X5EUS67RSTV5UXA34/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GP4JKTEO6X5EUS67RSTV5UXA34","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":"915ef67e9dd8ef81729a6a155a2ac40413400b8a4c3559767716300df3e8600a","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T11:27:41Z","title_canon_sha256":"e16a69044e72ccfde4e8c9e751767eb3c97fe26ed802997363e14b83356d36bc"},"schema_version":"1.0","source":{"id":"1802.10367","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10367","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10367v1","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10367","created_at":"2026-05-18T00:22:17Z"},{"alias_kind":"pith_short_12","alias_value":"GP4JKTEO6X5E","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GP4JKTEO6X5EUS67","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GP4JKTEO","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:635f93c78f9c4add9997cb976ee2760d0aba8f106dc28878bacc30ea0f4724bc","target":"graph","created_at":"2026-05-18T00:22:17Z","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":"Detecting objects and their 6D poses from only RGB images is an important task for many robotic applications. While deep learning methods have made significant progress in visual object detection and segmentation, the object pose estimation task is still challenging. In this paper, we introduce an end-toend deep learning framework, named Deep-6DPose, that jointly detects, segments, and most importantly recovers 6D poses of object instances from a single RGB image. In particular, we extend the recent state-of-the-art instance segmentation network Mask R-CNN with a novel pose estimation branch t","authors_text":"Ian Reid, Ming Cai, Thanh-Toan Do, Trung Pham","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T11:27:41Z","title":"Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10367","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:cde9f16342b17dc22fe5eb421684926d2b1c59fbf1507442d1f16ab03fea7270","target":"record","created_at":"2026-05-18T00:22:17Z","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":"915ef67e9dd8ef81729a6a155a2ac40413400b8a4c3559767716300df3e8600a","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-28T11:27:41Z","title_canon_sha256":"e16a69044e72ccfde4e8c9e751767eb3c97fe26ed802997363e14b83356d36bc"},"schema_version":"1.0","source":{"id":"1802.10367","kind":"arxiv","version":1}},"canonical_sha256":"33f8954c8ef5fa4a4bdf8ca75ed2e0df118131f7fb7de2306d7d504ce4855b14","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"33f8954c8ef5fa4a4bdf8ca75ed2e0df118131f7fb7de2306d7d504ce4855b14","first_computed_at":"2026-05-18T00:22:17.338498Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:22:17.338498Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9lC2k22zdEDBSZo+rxb/ReBJtDPAotd15YAA0EZitGFLGaQWliqpxYgJpzrnxJBeEj7zRy+GImUj1Mda/xR+Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:22:17.339142Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.10367","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cde9f16342b17dc22fe5eb421684926d2b1c59fbf1507442d1f16ab03fea7270","sha256:635f93c78f9c4add9997cb976ee2760d0aba8f106dc28878bacc30ea0f4724bc"],"state_sha256":"d9542c92618532fc2bb8b3cab87d385b365aa9c8a3bb948b2da78a6e15d7a755"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S/RQRbueOC+uXg/9mdVs4RSQkjEvy4uaCfMFFg4qChW0gWSZ4nvl5e3vThsi3JsmZLBlu2BbqfisKRm8rGF0Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T17:36:30.559190Z","bundle_sha256":"4a60b746c70ff129df6445e37a7421b24866a86cb1474dc0e96842233688fe3c"}}