{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:3TF2NBJ3WPZ4YYXGWP6J3GCOKK","short_pith_number":"pith:3TF2NBJ3","schema_version":"1.0","canonical_sha256":"dccba6853bb3f3cc62e6b3fc9d984e528c61d52a2d240610c344c15e6c2f0bd6","source":{"kind":"arxiv","id":"1804.06202","version":1},"attestation_state":"computed","paper":{"title":"IGCV$2$: Interleaved Structured Sparse Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guo-jun Qi, Guotian Xie, Jianhuang Lai, Jingdong Wang, Richang Hong, Ting Zhang","submitted_at":"2018-04-17T12:36:36Z","abstract_excerpt":"In this paper, we study the problem of designing efficient convolutional neural network architectures with the interest in eliminating the redundancy in convolution kernels. In addition to structured sparse kernels, low-rank kernels and the product of low-rank kernels, the product of structured sparse kernels, which is a framework for interpreting the recently-developed interleaved group convolutions (IGC) and its variants (e.g., Xception), has been attracting increasing interests.\n  Motivated by the observation that the convolutions contained in a group convolution in IGC can be further decom"},"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":"1804.06202","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-04-17T12:36:36Z","cross_cats_sorted":[],"title_canon_sha256":"be58db291c1d2703b30b1300cc28a5810dd3a90f494c5a7d1009527a2b083abe","abstract_canon_sha256":"4bd4068fb919999bb603c5cbc29bc24faedcc363fdbe811db0fb387ffed8e217"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:21.394843Z","signature_b64":"u4U96iKWYFadjpkd8ucZXeiwEeNlDjz3IRM00B/bOQVUilyKRKowJOGtE6hjY4GtoPzSUFxqyl01cAL0IyhrDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dccba6853bb3f3cc62e6b3fc9d984e528c61d52a2d240610c344c15e6c2f0bd6","last_reissued_at":"2026-05-18T00:18:21.394079Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:21.394079Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"IGCV$2$: Interleaved Structured Sparse Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guo-jun Qi, Guotian Xie, Jianhuang Lai, Jingdong Wang, Richang Hong, Ting Zhang","submitted_at":"2018-04-17T12:36:36Z","abstract_excerpt":"In this paper, we study the problem of designing efficient convolutional neural network architectures with the interest in eliminating the redundancy in convolution kernels. In addition to structured sparse kernels, low-rank kernels and the product of low-rank kernels, the product of structured sparse kernels, which is a framework for interpreting the recently-developed interleaved group convolutions (IGC) and its variants (e.g., Xception), has been attracting increasing interests.\n  Motivated by the observation that the convolutions contained in a group convolution in IGC can be further decom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.06202","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1804.06202","created_at":"2026-05-18T00:18:21.394205+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.06202v1","created_at":"2026-05-18T00:18:21.394205+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.06202","created_at":"2026-05-18T00:18:21.394205+00:00"},{"alias_kind":"pith_short_12","alias_value":"3TF2NBJ3WPZ4","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_16","alias_value":"3TF2NBJ3WPZ4YYXG","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_8","alias_value":"3TF2NBJ3","created_at":"2026-05-18T12:32:05.422762+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK","json":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK.json","graph_json":"https://pith.science/api/pith-number/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/graph.json","events_json":"https://pith.science/api/pith-number/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/events.json","paper":"https://pith.science/paper/3TF2NBJ3"},"agent_actions":{"view_html":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK","download_json":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK.json","view_paper":"https://pith.science/paper/3TF2NBJ3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.06202&json=true","fetch_graph":"https://pith.science/api/pith-number/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/graph.json","fetch_events":"https://pith.science/api/pith-number/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/action/storage_attestation","attest_author":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/action/author_attestation","sign_citation":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/action/citation_signature","submit_replication":"https://pith.science/pith/3TF2NBJ3WPZ4YYXGWP6J3GCOKK/action/replication_record"}},"created_at":"2026-05-18T00:18:21.394205+00:00","updated_at":"2026-05-18T00:18:21.394205+00:00"}