{"as_of":"2026-08-16T02:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2d538809edb606883147f589ebc04e35d8b6303414864b5937a6bc72d33e5668","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:22:39.850143Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.14854/citation-record","integrity":"/paper/2506.14854/integrity","json":"/paper/2506.14854/citation-record.json","paper":"/paper/2506.14854"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:36.010253Z","title":"Imagenet large scale visual recognition challenge.International journal of computer vision, 115:211–252, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.010253Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:12dcbc97b45dce5792eb1685461c97074ce8fc88dfe59b8acd7e67284cfef54c","observation_id":"836db931-2b8b-4565-8370-36fae460b572","resolution":{"observed_at":"2026-08-07T00:22:36.010253Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:36.124771Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.124771Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:c08c2bffa6cd194e35fe71caecf6603c2ece710f721e970a099ee3c77295ace4","observation_id":"903722e0-2275-44af-a8a1-0f1be04b646f","resolution":{"observed_at":"2026-08-07T00:22:36.124771Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:36.236708Z","title":"Simple online and realtime tracking with a deep association metric","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.236708Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:6f2a87e155b4732c96cbfc3ee8fd17c484fc9ac3551b777f87e1e0064fb88af3","observation_id":"4a516e52-766b-4cc1-b89a-4ae720da22ef","resolution":{"observed_at":"2026-08-07T00:22:36.236708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:44.872191Z","title":"The pascal visual object classes challenge: A retrospective.International journal of computer vision, 111:98–136, 2015","venue":null,"work_id":"fcb6918f-1734-423c-a2b7-f5caa9a8f030","year":2015},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.360174Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:72cc551cee05db90b692873e44b8db14ba995c35afe83f28605764e81c3aab4e","observation_id":"e427573b-f2a0-47a5-9f8e-2e13200f935c","resolution":{"observed_at":"2026-08-07T00:22:44.960757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:44.686065Z","title":"Video summarization using deep semantic features","venue":null,"work_id":"853ef2d3-a810-41e4-8e1e-417a7ddd10b2","year":2016},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.464746Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:78709574c24a7cce09a9d127dce9cb42ac2bd81ac4c79148b7ea9e323b36437f","observation_id":"b2ef9a58-58a7-4ba1-bfe9-5b4a2b85e974","resolution":{"observed_at":"2026-08-07T00:22:44.755621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:36.583867Z","title":"Drop an octave: Reducing spatial redundancy in convolutional neural networks with octave convolution","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.583867Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:540a3200cbddb366896c90fe39495eb6de06025d008e252a8642f2efb8acf5e0","observation_id":"d0c18b62-b4b1-4bfc-8c05-2be1406d963f","resolution":{"observed_at":"2026-08-07T00:22:36.583867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:36.671910Z","title":"Vivit: A video vision transformer","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.671910Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:bdeba0dfa45003e340b0f2039d491d0c10440bc7c79926958988d556d5717498","observation_id":"c305242a-6acf-409b-b62f-e9dd0fa67c36","resolution":{"observed_at":"2026-08-07T00:22:36.671910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:44.514095Z","title":"Time-contrastive networks: Self-supervised learning from video","venue":null,"work_id":"595f4674-6851-4240-a274-0d048717cd71","year":2018},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.854753Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:0149cc55771de75cc6af358e614f3fdb569a54f6280f548c854c22626b0455c2","observation_id":"ccfbd01a-5d34-40b2-ade3-ef161af669b1","resolution":{"observed_at":"2026-08-07T00:22:44.578603Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:44.299044Z","title":"Accurate 3d face reconstruction with weakly-supervised learning: From single image to image set","venue":null,"work_id":"c6a8a5ca-abe7-479e-921f-930dfc6e4b98","year":2019},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:36.960399Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:7bac528aabf8b1b93a85dbd4435cb736dd782f3288f9d9305dc81d1d7c2da25d","observation_id":"3b6eb999-464e-4fb4-8637-346e8959733c","resolution":{"observed_at":"2026-08-07T00:22:44.383983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:37.077493Z","title":"Training data-efficient image transformers & distillation through attention","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.077493Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:df9c30d5eb3b252795d0f17927f6aa6353a4b5ce5b3e59b991a9405af1ad65f4","observation_id":"653b60d2-ecd6-4291-9801-5c7bfbe335af","resolution":{"observed_at":"2026-08-07T00:22:37.077493Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:44.119859Z","title":"Large scale fine-grained categorization and domain-specific transfer learning","venue":null,"work_id":"d8e39a7e-8597-4b91-a988-0a1397ffe878","year":2018},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.199827Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:81e4502590fb89379bd85b7fd5f9acb2b4653cb368e950c6306c34c3b2ffea17","observation_id":"2044a422-e783-4e09-855d-4cb1e930532d","resolution":{"observed_at":"2026-08-07T00:22:44.200017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.11770","last_updated":"2020-02-19T18:59:52Z","snapshot_observed_at":"2026-08-13T05:46:24.009404Z","submitted_at":"2020-02-19T18:59:52Z","title":"Rethinking the Hyperparameters for Fine-tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.11770","snapshot_observed_at":"2026-08-07T00:22:37.321692Z","title":"Rethinking the hyperparameters for fine-tuning.arXiv preprint arXiv:2002.11770, 2020","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.321692Z"},"links":{"cited_paper":"/paper/2002.11770","citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:2947e988363fae9958672f69ffb7ede3044a06ddd5f6c44387bf87bb59171e99","observation_id":"586d881e-f31c-4e64-bfb9-a1518630b32e","resolution":{"observed_at":"2026-08-07T00:22:37.321692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:37.494010Z","title":"Model-agnostic meta-learning for fast adaptation of deep networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.494010Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:f62c8a9bec325d9c068b46dc3b76f37f58c5b53ea6ba9be1282592aadde593f2","observation_id":"e1645d80-45d8-43e5-a94c-e6ba282d9e33","resolution":{"observed_at":"2026-08-07T00:22:37.494010Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:37.562564Z","title":"Generalizing from a few examples: A survey on few-shot learning.ACM computing surveys (csur), 53(3):1–34, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.562564Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:7ddd4dbf24c2eb42912389163382b2b0ceb6b54e1b2c1484a4228e28eb794a5a","observation_id":"fa78ccc0-9573-4885-9f58-33ac3e39977f","resolution":{"observed_at":"2026-08-07T00:22:37.562564Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:43.953404Z","title":"Trackingnet: A large-scale dataset and benchmark for object tracking in the wild","venue":null,"work_id":"2aab1d23-d6f2-4272-acb9-023ea9bd5ddb","year":2018},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.663368Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:5cb4e4e3a31516fa0682f378a752f5052751d28b88d5869e83a8d0239e554d3b","observation_id":"020335ae-84c4-4795-a30c-0a44fd9727ca","resolution":{"observed_at":"2026-08-07T00:22:44.023481Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:43.776842Z","title":"Video annotation and tracking with active learning.Advances in Neural Information Processing Systems, 24, 2011","venue":null,"work_id":"fb390967-4b63-4e30-ba25-22dddddb537a","year":2011},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.767608Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:a90b9a76f27a8e0dbece1c286ac78a4e8a3d03fc0b0092b03cca70bcf370ca8a","observation_id":"036cd0f8-ab67-4f5f-9f94-a53e4c389dac","resolution":{"observed_at":"2026-08-07T00:22:43.839180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:43.605471Z","title":"Pathtrack: Fast trajectory annotation with path supervision","venue":null,"work_id":"e24c3845-a636-4f81-845e-4d8b757ddabc","year":2017},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:37.957293Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:e3f57fc4d337abd85cdfd21b30d964d065cb66c6c27d42117481dc5802c9444b","observation_id":"a30db224-f3b4-45e3-93fe-55218efb74d8","resolution":{"observed_at":"2026-08-07T00:22:43.685285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:43.410613Z","title":"A novel key-frames selection framework for comprehensive video summariza- tion.IEEE Transactions on Circuits and Systems for Video Technology, 30(2):577–589, 2019","venue":null,"work_id":"e1df174b-80eb-466c-987f-8f8d09e0d970","year":2019},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.109220Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:57b8472fc4e60e322e804f562438dcfbce1bec822fa96621793e72a405cb8497","observation_id":"8025805a-6d87-4fdd-8be1-5d6492d6824e","resolution":{"observed_at":"2026-08-07T00:22:43.506255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:43.168700Z","title":"A user attention model for video summarization","venue":null,"work_id":"2a2ac0e0-7579-4be7-a6e7-2991e42fe5de","year":2002},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.229916Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:2ffd7db986380f9761a16b1d96681f3d8dc23490d677d7dd5f8424c270bd16a8","observation_id":"9aa9d3a7-0af7-4a2c-a4a2-76c83906c01d","resolution":{"observed_at":"2026-08-07T00:22:43.291324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:42.889309Z","title":"Deep learning approach to key frame detection in human action videos.Recent Trends in Computational Intelligence, 1:1–17, 2020","venue":null,"work_id":"171438b7-e3d0-490e-b325-1a275e59d99c","year":2020},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.336697Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:da762f2da5c05c20996e78a7e1bfc69e4bd52e93fdf9170e8b7679fff14f364d","observation_id":"be4ddf3c-f10e-4787-a4ae-4b3dc205108a","resolution":{"observed_at":"2026-08-07T00:22:43.035579Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:42.621868Z","title":"Real-time keyframe extraction towards video content identifica- tion","venue":null,"work_id":"341cbc01-f1e8-4be2-a25e-dadc2a894eb3","year":2009},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.476567Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:dd717e31facc89aa1d562ea04c3947c6409f1ea2590e36ae765fc8bbe0b623fc","observation_id":"57b3b318-9973-4813-9d8f-b86b095f89f9","resolution":{"observed_at":"2026-08-07T00:22:42.759059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:42.323009Z","title":"Cnn based key frame extraction for face in video recognition","venue":null,"work_id":"e84d528c-dcf3-443b-aa91-afde2dce2746","year":2018},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.580126Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:26d4f0cc3f4737ae019eeaa3eccf7b842a8ec49681e7a5fa350763c61f5d50ab","observation_id":"44d074e5-e2ae-44a2-aab1-2ceb543a1dd5","resolution":{"observed_at":"2026-08-07T00:22:42.490002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:42.054644Z","title":"Keyframe-based video summarization with human in the loop","venue":null,"work_id":"1763bd6e-e8f7-466f-806c-fffff814c658","year":2018},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.726299Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:dc6d7f1e81f262f5c6c76b96bcc5bfa9c476df84e6513ed4934ca78381fc9b03","observation_id":"23622718-68e8-4e63-ad35-656b003dbc69","resolution":{"observed_at":"2026-08-07T00:22:42.142855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:41.809004Z","title":"An efficient keyframes selection based framework for video captioning","venue":null,"work_id":"696e0bfe-245f-4bc2-a1eb-645837aadf2a","year":2021},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.813943Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:26e71a9d1a251c4b597440f1c45db113633e3740181b24991b66d00b9569d6bb","observation_id":"51397c66-f3ef-49fc-aa8c-366cbaa5289c","resolution":{"observed_at":"2026-08-07T00:22:41.928828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:41.570617Z","title":"Self-supervised learning to detect key frames in videos.Sensors, 20(23):6941, 2020","venue":null,"work_id":"adf5ce26-b1e6-422d-94c0-98d8a342f97b","year":2020},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:38.937518Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:35aaaa75242dbc3251819f8ddd7a550c655aa97304640b4b4e1bb2effa7d6563","observation_id":"d0eb5444-7eab-4832-8cc4-03dc3510c405","resolution":{"observed_at":"2026-08-07T00:22:41.700338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:41.387614Z","title":"Deep unsupervised key frame extraction for efficient video classification.ACM Transactions on Multimedia Computing, Communications and Applications, 19(3):1–17, 2023","venue":null,"work_id":"58572f27-bd80-4014-9d41-adc3a4e674ca","year":2023},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.022658Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:dea07ebc3372acf14e36c24edc7ff33c1053295f9bab8a516e3b5a9264b52ad5","observation_id":"4b1bd19b-9195-4420-9f70-b00c7fe31d2d","resolution":{"observed_at":"2026-08-07T00:22:41.526049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:41.245244Z","title":"Unsupervised video summarization framework using keyframe extraction and video skimming","venue":null,"work_id":"43c6dea4-abb8-4c6f-abd9-ec165afef431","year":2020},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.089115Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:6e9f30b8409264a17c207d1d3d115562e43080a81f566db128b61832e5a34830","observation_id":"54effa41-4b34-4a79-a60c-701188e788c8","resolution":{"observed_at":"2026-08-07T00:22:41.308901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:41.061924Z","title":"Interested keyframe extraction of commodity video based on adaptive clustering annotation.Applied Sciences, 12(3):1502, 2022","venue":null,"work_id":"cd201b37-09dd-4d6d-ac86-740a5ecc2c96","year":2022},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.154747Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:b8242ff3ccd8240d10a49b03d2a0508f844a2a37b6f607138457f2a83e4d5ea0","observation_id":"d9557519-40ff-488a-b7d6-390f94fdddd1","resolution":{"observed_at":"2026-08-07T00:22:41.169962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:40.833172Z","title":"Summarizing videos with attention","venue":null,"work_id":"3588378e-b7b8-4119-b84d-c0c83bdf973f","year":2018},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.241222Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:9be2c8954494b48e1088dbaeb2880d81d177faefc2ab6d440cc6e12c93af7c45","observation_id":"3c5b6aa5-f8b6-4838-b802-b62c3707acd1","resolution":{"observed_at":"2026-08-07T00:22:40.943623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:40.625866Z","title":"Online learnable keyframe extraction in videos and its application with semantic word vector in action recognition.Pattern Recognition, 122:108273, 2022","venue":null,"work_id":"257556f0-3744-4760-ac43-78c0fbbf0617","year":2022},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.302737Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:f3149262e0cc14473f1c3f70a672af3c8eaab168ba1a6842f667e86daea18272","observation_id":"39b5c83a-b722-4514-a31f-dca7e37c677d","resolution":{"observed_at":"2026-08-07T00:22:40.714007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:40.464191Z","title":"A review of research on object detection based on deep learning","venue":null,"work_id":"8190fec0-a322-41e9-922b-9bb33487ea84","year":2020},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.392467Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:012bf38a082e07b4079b80d71847586696ad5d0963cb2f037356b76d1287ec3d","observation_id":"787ef37b-99b3-4b4e-a553-cd4bf3344f25","resolution":{"observed_at":"2026-08-07T00:22:40.510953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:39.547227Z","title":"Rethinking the inception architecture for computer vision","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.547227Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:21f461edc319a62f9c023336cebfd4591e833a6aa838ea864f6b78b454fdebc2","observation_id":"ce0e9beb-34ce-4a7f-a1ba-2bd45a8aaa01","resolution":{"observed_at":"2026-08-07T00:22:39.547227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.02643","last_updated":"2023-04-05T17:59:46Z","snapshot_observed_at":"2026-08-08T05:14:59.435033Z","submitted_at":"2023-04-05T17:59:46Z","title":"Segment Anything","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.02643","snapshot_observed_at":"2026-08-07T00:22:39.693470Z","title":"Segment anything.arXiv preprint arXiv:2304.02643, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.693470Z"},"links":{"cited_paper":"/paper/2304.02643","citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:00462f330613439c3b3ffbd51bd75fb29f2809677fd51291045b8785b5644bf6","observation_id":"7f3ba1e8-4136-4a2c-8d55-1323eac93797","resolution":{"observed_at":"2026-08-07T00:22:39.693470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:40.289891Z","title":"End-to-end object detection with transformers","venue":null,"work_id":"fe05a484-dae9-4c1a-ad27-8502d79707a9","year":2020},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.762463Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:7177103d64695073502a73944b51073f164096a8a4db655473aad531861549ed","observation_id":"4f677349-bb31-4790-93a3-56c99f58cde9","resolution":{"observed_at":"2026-08-07T00:22:40.356692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:22:40.015293Z","title":"Ultralytics/YOLOv5: v5.0","venue":null,"work_id":"d70fbb0d-a908-4840-a643-101b3ca9c4ff","year":2021},"citing_paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T00:22:39.850143Z"},"links":{"citing_paper":"/paper/2506.14854"},"observation_digest":"sha256:dd9db8642e8eae54b9609fd5112216b27c365fdd76d98c4c37dfd2c8ec2b1039","observation_id":"33a079eb-9dad-4d8c-b284-a2b6b0ee2329","resolution":{"observed_at":"2026-08-07T00:22:40.148496Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.14854","last_updated":"2025-06-19T04:04:23Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T03:08:48.143478Z","submitted_at":"2025-06-17T06:42:58Z","title":"Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":24},"total_outbound_references":35},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.14854."}