{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:LZAJXQUTKXKU56TJA5URUUZTKI","short_pith_number":"pith:LZAJXQUT","canonical_record":{"source":{"id":"1604.03351","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-12T11:43:14Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"31d219ecf5b0114b982a6f16a53311539a5a967f6b94f0c81b562d624f91169d","abstract_canon_sha256":"81d5d989e064bc7d0845609de8b641760d08396f78d24f55fcddf12cec6cf519"},"schema_version":"1.0"},"canonical_sha256":"5e409bc29355d54efa6907691a53335203d99803fc48be9c5993a05c9ea456c3","source":{"kind":"arxiv","id":"1604.03351","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.03351","created_at":"2026-05-18T00:32:26Z"},{"alias_kind":"arxiv_version","alias_value":"1604.03351v2","created_at":"2026-05-18T00:32:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.03351","created_at":"2026-05-18T00:32:26Z"},{"alias_kind":"pith_short_12","alias_value":"LZAJXQUTKXKU","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_16","alias_value":"LZAJXQUTKXKU56TJ","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_8","alias_value":"LZAJXQUT","created_at":"2026-05-18T12:30:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:LZAJXQUTKXKU56TJA5URUUZTKI","target":"record","payload":{"canonical_record":{"source":{"id":"1604.03351","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-12T11:43:14Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"31d219ecf5b0114b982a6f16a53311539a5a967f6b94f0c81b562d624f91169d","abstract_canon_sha256":"81d5d989e064bc7d0845609de8b641760d08396f78d24f55fcddf12cec6cf519"},"schema_version":"1.0"},"canonical_sha256":"5e409bc29355d54efa6907691a53335203d99803fc48be9c5993a05c9ea456c3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:26.153796Z","signature_b64":"KBbF6+f9Nlqcj11Hq+PiW0vKNFlCjZRagc86ZLVLgdAkUShtmuK1WOg2vBb/+0QmdEaUSSn2POJTx346A35nDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5e409bc29355d54efa6907691a53335203d99803fc48be9c5993a05c9ea456c3","last_reissued_at":"2026-05-18T00:32:26.152981Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:26.152981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1604.03351","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":"2026-05-18T00:32:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KZ/yJ6L4/UmdG7qNlnJRThOvDhq5XdOc9ahCETFAu1gSvJihUvtKEYL/qHzrXI02CgTdpWl/+PqKdCgbkm2LDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T13:50:36.738488Z"},"content_sha256":"e6cf312d0c190e6ce5a682b4051f3a1534104ddd2e280a30575caabb3540ba02","schema_version":"1.0","event_id":"sha256:e6cf312d0c190e6ce5a682b4051f3a1534104ddd2e280a30575caabb3540ba02"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:LZAJXQUTKXKU56TJA5URUUZTKI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Orientation-boosted Voxel Nets for 3D Object Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.CV","authors_text":"Ehsan Amiri, Mohammadreza Zolfaghari, Nima Sedaghat, Thomas Brox","submitted_at":"2016-04-12T11:43:14Z","abstract_excerpt":"Recent work has shown good recognition results in 3D object recognition using 3D convolutional networks. In this paper, we show that the object orientation plays an important role in 3D recognition. More specifically, we argue that objects induce different features in the network under rotation. Thus, we approach the category-level classification task as a multi-task problem, in which the network is trained to predict the pose of the object in addition to the class label as a parallel task. We show that this yields significant improvements in the classification results. We test our suggested a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.03351","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":"2026-05-18T00:32:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oNQInTXulW/TWyIfiWaJZP03BeuvQd3YnIWTrKd35Eo5Ad5lckj+YF5hsVXdRQobxWxn0ZKoEEYgq4F2cdDJBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T13:50:36.739417Z"},"content_sha256":"0b9d9b403fd3bbe8cf956ba005e09c66c182312523276c08df77fbb1c200c6a5","schema_version":"1.0","event_id":"sha256:0b9d9b403fd3bbe8cf956ba005e09c66c182312523276c08df77fbb1c200c6a5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LZAJXQUTKXKU56TJA5URUUZTKI/bundle.json","state_url":"https://pith.science/pith/LZAJXQUTKXKU56TJA5URUUZTKI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LZAJXQUTKXKU56TJA5URUUZTKI/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":"2026-08-20T13:50:36Z","links":{"resolver":"https://pith.science/pith/LZAJXQUTKXKU56TJA5URUUZTKI","bundle":"https://pith.science/pith/LZAJXQUTKXKU56TJA5URUUZTKI/bundle.json","state":"https://pith.science/pith/LZAJXQUTKXKU56TJA5URUUZTKI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LZAJXQUTKXKU56TJA5URUUZTKI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:LZAJXQUTKXKU56TJA5URUUZTKI","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":"81d5d989e064bc7d0845609de8b641760d08396f78d24f55fcddf12cec6cf519","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-12T11:43:14Z","title_canon_sha256":"31d219ecf5b0114b982a6f16a53311539a5a967f6b94f0c81b562d624f91169d"},"schema_version":"1.0","source":{"id":"1604.03351","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.03351","created_at":"2026-05-18T00:32:26Z"},{"alias_kind":"arxiv_version","alias_value":"1604.03351v2","created_at":"2026-05-18T00:32:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.03351","created_at":"2026-05-18T00:32:26Z"},{"alias_kind":"pith_short_12","alias_value":"LZAJXQUTKXKU","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_16","alias_value":"LZAJXQUTKXKU56TJ","created_at":"2026-05-18T12:30:29Z"},{"alias_kind":"pith_short_8","alias_value":"LZAJXQUT","created_at":"2026-05-18T12:30:29Z"}],"graph_snapshots":[{"event_id":"sha256:0b9d9b403fd3bbe8cf956ba005e09c66c182312523276c08df77fbb1c200c6a5","target":"graph","created_at":"2026-05-18T00:32:26Z","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":"Recent work has shown good recognition results in 3D object recognition using 3D convolutional networks. In this paper, we show that the object orientation plays an important role in 3D recognition. More specifically, we argue that objects induce different features in the network under rotation. Thus, we approach the category-level classification task as a multi-task problem, in which the network is trained to predict the pose of the object in addition to the class label as a parallel task. We show that this yields significant improvements in the classification results. We test our suggested a","authors_text":"Ehsan Amiri, Mohammadreza Zolfaghari, Nima Sedaghat, Thomas Brox","cross_cats":["cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-12T11:43:14Z","title":"Orientation-boosted Voxel Nets for 3D Object Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.03351","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:e6cf312d0c190e6ce5a682b4051f3a1534104ddd2e280a30575caabb3540ba02","target":"record","created_at":"2026-05-18T00:32:26Z","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":"81d5d989e064bc7d0845609de8b641760d08396f78d24f55fcddf12cec6cf519","cross_cats_sorted":["cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-12T11:43:14Z","title_canon_sha256":"31d219ecf5b0114b982a6f16a53311539a5a967f6b94f0c81b562d624f91169d"},"schema_version":"1.0","source":{"id":"1604.03351","kind":"arxiv","version":2}},"canonical_sha256":"5e409bc29355d54efa6907691a53335203d99803fc48be9c5993a05c9ea456c3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5e409bc29355d54efa6907691a53335203d99803fc48be9c5993a05c9ea456c3","first_computed_at":"2026-05-18T00:32:26.152981Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:32:26.152981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KBbF6+f9Nlqcj11Hq+PiW0vKNFlCjZRagc86ZLVLgdAkUShtmuK1WOg2vBb/+0QmdEaUSSn2POJTx346A35nDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:32:26.153796Z","signed_message":"canonical_sha256_bytes"},"source_id":"1604.03351","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e6cf312d0c190e6ce5a682b4051f3a1534104ddd2e280a30575caabb3540ba02","sha256:0b9d9b403fd3bbe8cf956ba005e09c66c182312523276c08df77fbb1c200c6a5"],"state_sha256":"40c1628a1e80f960a8be49b32a130466a0b74b8c6be0b27d3a469663fad6db04"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rZ6yaT+5f/W5G3SsaWHwYc5kiRgP4vw5FVC3dnUcBu5EFQ3GT7Re5TUac7jF8/psPoK0MQ3Sj8toWf3ig7rFDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T13:50:36.745685Z","bundle_sha256":"6a437451b5c71b763dd945542a308f8c22b2ea6bac718cf5e95cb1e2d5010a57"}}