{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:X2LAPU3WKZBJTO7X5FCDBPVMPF","short_pith_number":"pith:X2LAPU3W","schema_version":"1.0","canonical_sha256":"be9607d376564299bbf7e94430beac7947bc4a25a4e9e1613f797c0111a76108","source":{"kind":"arxiv","id":"2105.02788","version":1},"attestation_state":"computed","paper":{"title":"ACORN: Adaptive Coordinate Networks for Neural Scene Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Connor Z. Lin, David B. Lindell, Eric R. Chan, Gordon Wetzstein, Julien N. P. Martel, Marco Monteiro","submitted_at":"2021-05-06T16:21:38Z","abstract_excerpt":"Neural representations have emerged as a new paradigm for applications in rendering, imaging, geometric modeling, and simulation. Compared to traditional representations such as meshes, point clouds, or volumes they can be flexibly incorporated into differentiable learning-based pipelines. While recent improvements to neural representations now make it possible to represent signals with fine details at moderate resolutions (e.g., for images and 3D shapes), adequately representing large-scale or complex scenes has proven a challenge. Current neural representations fail to accurately represent i"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2105.02788","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-06T16:21:38Z","cross_cats_sorted":["cs.GR","cs.LG"],"title_canon_sha256":"de2ff2f0bc9256483eb80f01d869aeee333e459e3c765caf58409faa3d6d8b8b","abstract_canon_sha256":"efc51dffa00aa100098b89317cb6c75aa528aa2f4d069fd0fbb1aaece3a826e7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:38:10.373405Z","signature_b64":"QsGoX8IdaaXwHX7uFEp1LL7lUqP6udIctwcIqNdktk7WJtyex72aUpxHWLFqfg46VdPBMb4pUhuz9hmyFAQ8Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"be9607d376564299bbf7e94430beac7947bc4a25a4e9e1613f797c0111a76108","last_reissued_at":"2026-07-05T02:38:10.372809Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:38:10.372809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ACORN: Adaptive Coordinate Networks for Neural Scene Representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Connor Z. Lin, David B. Lindell, Eric R. Chan, Gordon Wetzstein, Julien N. P. Martel, Marco Monteiro","submitted_at":"2021-05-06T16:21:38Z","abstract_excerpt":"Neural representations have emerged as a new paradigm for applications in rendering, imaging, geometric modeling, and simulation. Compared to traditional representations such as meshes, point clouds, or volumes they can be flexibly incorporated into differentiable learning-based pipelines. While recent improvements to neural representations now make it possible to represent signals with fine details at moderate resolutions (e.g., for images and 3D shapes), adequately representing large-scale or complex scenes has proven a challenge. Current neural representations fail to accurately represent i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.02788","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/2105.02788/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2105.02788","created_at":"2026-07-05T02:38:10.372890+00:00"},{"alias_kind":"arxiv_version","alias_value":"2105.02788v1","created_at":"2026-07-05T02:38:10.372890+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.02788","created_at":"2026-07-05T02:38:10.372890+00:00"},{"alias_kind":"pith_short_12","alias_value":"X2LAPU3WKZBJ","created_at":"2026-07-05T02:38:10.372890+00:00"},{"alias_kind":"pith_short_16","alias_value":"X2LAPU3WKZBJTO7X","created_at":"2026-07-05T02:38:10.372890+00:00"},{"alias_kind":"pith_short_8","alias_value":"X2LAPU3W","created_at":"2026-07-05T02:38:10.372890+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":9,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.06671","citing_title":"JA-SIREN: Deterministic Initialization for Sinusoidal Networks via Spectral Matching","ref_index":5,"is_internal_anchor":false},{"citing_arxiv_id":"2205.13524","citing_title":"PREF: Phasorial Embedding Fields for Compact Neural Representations","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2605.16258","citing_title":"IVGT: Implicit Visual Geometry Transformer for Neural Scene Representation","ref_index":10,"is_internal_anchor":false},{"citing_arxiv_id":"2605.22556","citing_title":"ImplicitTerrainV2: Wavelet-Guided Spatially Adaptive Neural Terrain Representation","ref_index":54,"is_internal_anchor":false},{"citing_arxiv_id":"2605.20820","citing_title":"AIR: Amortized Image Reconstruction Framework for Self-Supervised Feed-Forward 2D Gaussian Splatting","ref_index":18,"is_internal_anchor":false},{"citing_arxiv_id":"2605.16258","citing_title":"IVGT: Implicit Visual Geometry Transformer for Neural Scene Representation","ref_index":9,"is_internal_anchor":false},{"citing_arxiv_id":"2605.13988","citing_title":"Neural Fields for NV-Center Inverse Sensing","ref_index":47,"is_internal_anchor":false},{"citing_arxiv_id":"2604.21984","citing_title":"Soft Anisotropic Diagrams for Differentiable Image Representation","ref_index":14,"is_internal_anchor":false},{"citing_arxiv_id":"2604.15047","citing_title":"Implicit Neural Representations: A Signal Processing Perspective","ref_index":27,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF","json":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF.json","graph_json":"https://pith.science/api/pith-number/X2LAPU3WKZBJTO7X5FCDBPVMPF/graph.json","events_json":"https://pith.science/api/pith-number/X2LAPU3WKZBJTO7X5FCDBPVMPF/events.json","paper":"https://pith.science/paper/X2LAPU3W"},"agent_actions":{"view_html":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF","download_json":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF.json","view_paper":"https://pith.science/paper/X2LAPU3W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2105.02788&json=true","fetch_graph":"https://pith.science/api/pith-number/X2LAPU3WKZBJTO7X5FCDBPVMPF/graph.json","fetch_events":"https://pith.science/api/pith-number/X2LAPU3WKZBJTO7X5FCDBPVMPF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF/action/storage_attestation","attest_author":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF/action/author_attestation","sign_citation":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF/action/citation_signature","submit_replication":"https://pith.science/pith/X2LAPU3WKZBJTO7X5FCDBPVMPF/action/replication_record"}},"created_at":"2026-07-05T02:38:10.372890+00:00","updated_at":"2026-07-05T02:38:10.372890+00:00"}