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Paper Citation Record · LEDGER

Recognizing Part Attributes with Insufficient Data

As of 17 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:1908.03335.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1908.03335 v2

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:21:44.640182Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

70 of 70 outbound references displayed

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  • verified fuzzy58
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d50e314c-7e6c-4d31-a720-97fa313746c2 · outbound

This paper cites How to transfer? zero-shot object recognition via hierarchical transfer of se- mantic attributes.

Recognizing Part Attributes with Insufficient Data How to transfer? zero-shot object recognition via hierarchical transfer of se- mantic attributes

Reference 1

Resolution
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Source-reported events for the cited work

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Observation 94f2f4b9-38cd-4495-960a-1c878ed780c6 · outbound

This paper cites Neural module networks.

Recognizing Part Attributes with Insufficient Data Neural module networks

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5caa0b23-59a3-4658-9cfa-427627e59b6a · outbound

This paper cites Vqa: Visual question answering.

Recognizing Part Attributes with Insufficient Data Vqa: Visual question answering

Reference 3

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Source-reported events for the cited work

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Observation 4c7c3e1d-6fbb-4e1c-a0b6-7477c08258b5 · outbound

This paper cites Multiple Object Recognition with Visual Attention.

Recognizing Part Attributes with Insufficient Data Multiple Object Recognition with Visual Attention

Reference 4

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Source-reported events for the cited work

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Observation 6286bf50-a4fd-4283-9446-d0a60627ac1d · outbound

This paper cites De- scribing people: A poselet-based approach to attribute clas- sification.

Recognizing Part Attributes with Insufficient Data De- scribing people: A poselet-based approach to attribute clas- sification

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 46f7f7ce-1fb8-495a-96c4-db8f961ffbea · outbound

This paper cites Poselets: Body part detectors trained using 3d human pose annotations.

Recognizing Part Attributes with Insufficient Data Poselets: Body part detectors trained using 3d human pose annotations

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 096a6510-9e04-4851-9dce-6437c418ddc8 · outbound

This paper cites An empirical study and analysis of generalized zero- shot learning for object recognition in the wild.

Recognizing Part Attributes with Insufficient Data An empirical study and analysis of generalized zero- shot learning for object recognition in the wild

Reference 7

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 928f32d3-ec8f-4f4a-9365-29f0f6a60e33 · outbound

This paper cites ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering.

Recognizing Part Attributes with Insufficient Data ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ff345dcf-f5cd-4f7c-8288-101284c2fa96 · outbound

This paper cites Pedestrian attribute recognition at far distance.

Recognizing Part Attributes with Insufficient Data Pedestrian attribute recognition at far distance

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 2275ae38-eaaa-48b5-9c2a-53c7227b5a2a · outbound

This paper cites Attribute-centric recognition for cross-category generalization.

Recognizing Part Attributes with Insufficient Data Attribute-centric recognition for cross-category generalization

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 181ef280-a0ae-4427-b965-55f0f5ca5b2b · outbound

This paper cites Describing objects by their attributes.

Recognizing Part Attributes with Insufficient Data Describing objects by their attributes

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1b66a726-4bdc-4ab7-bae3-f36e3f28359b · outbound

This paper cites Learning visual at- tributes.

Recognizing Part Attributes with Insufficient Data Learning visual at- tributes

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation cb7311d0-2ecc-43bf-97a2-edcb32a8ba22 · outbound

This paper cites Model- agnostic meta-learning for fast adaptation of deep networks.

Recognizing Part Attributes with Insufficient Data Model- agnostic meta-learning for fast adaptation of deep networks

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 97d27e08-b5f2-4893-b1df-1cb192f189ec · outbound

This paper cites Fine-grained recognition in the wild: A multi-task domain adaptation ap- proach.

Recognizing Part Attributes with Insufficient Data Fine-grained recognition in the wild: A multi-task domain adaptation ap- proach

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 2f52946f-2d7d-4547-8c86-d6fc07353edb · outbound

This paper cites Fast r-cnn.

Recognizing Part Attributes with Insufficient Data Fast r-cnn

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation db769639-67a9-40de-b06a-b0fb7da225df · outbound

This paper cites Region-based convolutional networks for accurate object detection and segmentation.

Recognizing Part Attributes with Insufficient Data Region-based convolutional networks for accurate object detection and segmentation

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5dc53d10-4183-48ec-aee5-3a7071c1d051 · outbound

This paper cites Evaluating ap- pearance models for recognition, reacquisition, and track- ing.

Recognizing Part Attributes with Insufficient Data Evaluating ap- pearance models for recognition, reacquisition, and track- ing

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f1843463-4ee4-4c73-9b12-856e3d6b1b7d · outbound

This paper cites Attributes for improved attributes: A multi-task network utilizing implicit and ex- plicit relationships for facial attribute classification.

Recognizing Part Attributes with Insufficient Data Attributes for improved attributes: A multi-task network utilizing implicit and ex- plicit relationships for facial attribute classification

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4ba56db0-2fc6-4e95-802d-1227f4f53f46 · outbound

This paper cites A simple general approach to inference about the tail of a distribution.The annals of statistics, pages 1163– 1174, 1975.

Recognizing Part Attributes with Insufficient Data A simple general approach to inference about the tail of a distribution.The annals of statistics, pages 1163– 1174, 1975

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 25f9397a-70a3-45ba-9b8a-0283e4be4e4f · outbound

This paper cites Labeled faces in the wild: A database forstudying face recognition in unconstrained environments.

Recognizing Part Attributes with Insufficient Data Labeled faces in the wild: A database forstudying face recognition in unconstrained environments

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 97ebec24-c7fd-4f9a-9617-154f7dd660eb · outbound

This paper cites Spatial transformer networks.

Recognizing Part Attributes with Insufficient Data Spatial transformer networks

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 26d3ef0e-b3e7-4b8c-9f24-c05b0cc81c3f · outbound

This paper cites Human attribute recognition by rich appearance dictionary.

Recognizing Part Attributes with Insufficient Data Human attribute recognition by rich appearance dictionary

Reference 22

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 41f13646-8f1d-4726-86fb-1690fab481c3 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Recognizing Part Attributes with Insufficient Data Adam: A Method for Stochastic Optimization

Reference 23

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Source-reported events for the cited work

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Observation 6c8c03bc-d5b8-4b6c-bb04-5261fd259842 · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

Recognizing Part Attributes with Insufficient Data Imagenet classification with deep convolutional neural net- works

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 376cadc1-2f1a-46f5-beb5-284097fcda26 · outbound

This paper cites Describable visual attributes for face verifica- tion and image search.

Recognizing Part Attributes with Insufficient Data Describable visual attributes for face verifica- tion and image search

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f553f336-8dc6-459b-be7c-8915fb4b0bb2 · outbound

This paper cites Attribute and simile classifiers for face veri- fication.

Recognizing Part Attributes with Insufficient Data Attribute and simile classifiers for face veri- fication

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation b957c66b-52bd-460f-9d3b-24bd3b85a649 · outbound

This paper cites Learning to detect unseen object classes by between- class attribute transfer.

Recognizing Part Attributes with Insufficient Data Learning to detect unseen object classes by between- class attribute transfer

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 361311fd-85e3-4fc7-90ed-a843e6bf9389 · outbound

This paper cites Attribute-based classification for zero-shot visual object categorization.

Recognizing Part Attributes with Insufficient Data Attribute-based classification for zero-shot visual object categorization

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 293a820a-2778-4fde-9baf-2a121a27e269 · outbound

This paper cites A Richly Annotated Dataset for Pedestrian Attribute Recognition.

Recognizing Part Attributes with Insufficient Data A Richly Annotated Dataset for Pedestrian Attribute Recognition

Reference 29

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 24180b81-7224-4259-bfe0-3b892103388f · outbound

This paper cites Human attribute recognition by deep hierarchical con- texts.

Recognizing Part Attributes with Insufficient Data Human attribute recognition by deep hierarchical con- texts

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4e33333e-3c54-493f-86c3-7bf7d9340022 · outbound

This paper cites Zero-shot recognition using dual visual- semantic mapping paths.

Recognizing Part Attributes with Insufficient Data Zero-shot recognition using dual visual- semantic mapping paths

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:46.017636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation ae37706b-320c-447d-ac35-55b48fbbe21b · outbound

This paper cites Localizing by describing: Attribute-guided attention lo- calization for fine-grained recognition.

Recognizing Part Attributes with Insufficient Data Localizing by describing: Attribute-guided attention lo- calization for fine-grained recognition

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.991843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4091cc68-8bdb-4623-8d0f-577a4fcc0ad3 · outbound

This paper cites Fully Convolutional Attention Networks for Fine-Grained Recognition.

Recognizing Part Attributes with Insufficient Data Fully Convolutional Attention Networks for Fine-Grained Recognition

Reference 33

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c9b6c6ee-95e6-4643-ae23-5e428a615868 · outbound

This paper cites Deepfashion: Powering robust clothes recognition and retrieval with rich annotations.

Recognizing Part Attributes with Insufficient Data Deepfashion: Powering robust clothes recognition and retrieval with rich annotations

Reference 34

Resolution
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no resolver link, observed 2026-08-14T14:21:44.365083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 0b8a2861-d1cd-4c7d-9612-11cfb92563ad · outbound

This paper cites Deep learning face attributes in the wild.

Recognizing Part Attributes with Insufficient Data Deep learning face attributes in the wild

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.950505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c4d8ef2a-4ee5-4b32-82fe-015944f532ad · outbound

This paper cites Fully-adaptive feature shar- ing in multi-task networks with applications in person at- tribute classification.

Recognizing Part Attributes with Insufficient Data Fully-adaptive feature shar- ing in multi-task networks with applications in person at- tribute classification

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.904307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.391173Z digest=sha256:be2c677b67f1d87ccc2b4525c333f71720dfdb105058a5b879835f4f6b594c39

Observation 19b42497-8b11-4e11-b8b3-aafa46601787 · outbound

This paper cites Transparency by design: Closing the gap be- tween performance and interpretability in visual reasoning.

Recognizing Part Attributes with Insufficient Data Transparency by design: Closing the gap be- tween performance and interpretability in visual reasoning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.879371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.397934Z digest=sha256:1755a7ae7784403189a6b8dd921d2c1d01722bef382ba99e69b05f2857b85391

Observation 6b4ce273-bb76-4861-a4c8-6a90e47ac1df · outbound

This paper cites Re- current models of visual attention.

Recognizing Part Attributes with Insufficient Data Re- current models of visual attention

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.789119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.406364Z digest=sha256:234cb481292fd3e6bd699d12243107f829c514f356f0aa393246877d86f80a31

Observation c1c3e85a-57e8-418c-acbd-30f71b67d293 · outbound

This paper cites Zero-shot learning with semantic output codes.

Recognizing Part Attributes with Insufficient Data Zero-shot learning with semantic output codes

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.764942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.414397Z digest=sha256:80564fb90ce8971e26d634662678c35051989f0c65f4c37b7aab6c703cf4b282

Observation 363a1830-e72c-4e17-ac6c-c5ff7512dad7 · outbound

This paper cites Sun attribute database: Discovering, annotating, and recognizing scene attributes.

Recognizing Part Attributes with Insufficient Data Sun attribute database: Discovering, annotating, and recognizing scene attributes

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.724301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.420165Z digest=sha256:a8b043d09edb17c4f2c74d52994608ae5574c6ca93632a051f6a0499c1a340a3

Observation 035fcdf9-6d84-4b1c-8c01-6966167bcd7a · outbound

This paper cites Coco attributes: At- tributes for people, animals, and objects.

Recognizing Part Attributes with Insufficient Data Coco attributes: At- tributes for people, animals, and objects

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.682280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.425377Z digest=sha256:a39e2828f2e498e45d3f26618f64c3afa2bc79c0566f66ef8eb9a9af658bd6a7

Observation 7343ab3f-155f-4079-b94a-bb9deb95671b · outbound

This paper cites Optimization as a model for few-shot learning.

Recognizing Part Attributes with Insufficient Data Optimization as a model for few-shot learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.646700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c94882a6-978d-4b1c-8fe3-972583d8f113 · outbound

This paper cites You only look once: Unified, real-time object de- tection.

Recognizing Part Attributes with Insufficient Data You only look once: Unified, real-time object de- tection

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.613050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.440861Z digest=sha256:61bd5bcf87435de6dd7f518da2f4a3ea5516ebac7c128e1a5083923e3b31f984

Observation 6d9a4739-84e9-40b0-b9ae-f58f744815d8 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Recognizing Part Attributes with Insufficient Data Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.591253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.447603Z digest=sha256:5765e3a03e300b475e75356a9b0a1c5fd115e38b4270c1b5c00dcbbd3c4654e2

Observation b66b79d0-982e-40a7-8e45-52e0516ca4f7 · outbound

This paper cites An embarrass- ingly simple approach to zero-shot learning.

Recognizing Part Attributes with Insufficient Data An embarrass- ingly simple approach to zero-shot learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.560265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.453458Z digest=sha256:b9d42a38f22d89352f0f7cde416658b765b83c1af0ef43a71c7bd5129a2a5f8d

Observation 21fbce01-fc98-4ef2-b133-a91b064a34d0 · outbound

This paper cites Attribute learning in large-scale datasets.

Recognizing Part Attributes with Insufficient Data Attribute learning in large-scale datasets

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.533565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.459602Z digest=sha256:5cb315bcc83361db60a709955a0b243218245675a5abcfdf70d6f8cc40b5587c

Observation 4474dd6f-bc9f-4f71-ad30-0020dea5277e · outbound

This paper cites Attention for Fine-Grained Categorization.

Recognizing Part Attributes with Insufficient Data Attention for Fine-Grained Categorization

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-14T14:21:44.464772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:21:44.464772Z digest=sha256:261e10c92ccf9cbe1c25ea9c0e1b483ee755c99cb1e3b4283eafd0e29d2de964

Observation 2a9c1d3e-6bb9-4b7e-8a06-b5a10ac496e2 · outbound

This paper cites Learning discriminative spatial representation for image classification.

Recognizing Part Attributes with Insufficient Data Learning discriminative spatial representation for image classification

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.506087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.471065Z digest=sha256:f32e7e1c216f4f80b219c099b5d011bdafa5860205d70d48a2d7ee0043796812

Observation 7c44223c-cf65-4dfc-8d25-df1c43fcc9c8 · outbound

This paper cites Per- son attribute recognition with a jointly-trained holistic cnn model.

Recognizing Part Attributes with Insufficient Data Per- son attribute recognition with a jointly-trained holistic cnn model

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.481832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.477380Z digest=sha256:54987c76b693d1badb5475083b49328fdedcef6fbdcf908560fb53c67002cc8a

Observation 746d4785-9279-4eb5-aeea-f144301589d8 · outbound

This paper cites Is learning the n-th thing any easier than learning the first? In NIPS, pages 640–646, 1996.

Recognizing Part Attributes with Insufficient Data Is learning the n-th thing any easier than learning the first? In NIPS, pages 640–646, 1996

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.448734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.489605Z digest=sha256:71d97b77e50d7a523e1b3d4cef51556b800af62f091ba70a49e8f378294e8452

Observation d13e4f83-b0f2-4bf4-a682-5f7ecffe8606 · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

Recognizing Part Attributes with Insufficient Data The caltech-ucsd birds-200-2011 dataset

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.421017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.505454Z digest=sha256:743b6419366af86ca2c1141e1d528b10cbd9d5cc80368e5addc77967f6505a64

Observation 360de896-b339-4294-a505-17ab37e6cdb4 · outbound

This paper cites Relational knowledge transfer for zero-shot learning.

Recognizing Part Attributes with Insufficient Data Relational knowledge transfer for zero-shot learning

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.392992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.516426Z digest=sha256:6b18fb75d49941bb0a6218d7d2ad3463d793924807707a6c60953b6570b6c6d5

Observation 99fe9497-9e60-4a88-b245-9c8b2c3d52b4 · outbound

This paper cites Residual attention network for image classification.

Recognizing Part Attributes with Insufficient Data Residual attention network for image classification

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.362820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.524273Z digest=sha256:af6ff8a65e53159666d006cd6bed5e52df3f3e63422f9be28078a386f4fb091d

Observation ae4b6960-a60d-4f2d-98cd-ee6f7feab1ec · outbound

This paper cites Learn- ing models for object recognition from natural language de- scriptions.

Recognizing Part Attributes with Insufficient Data Learn- ing models for object recognition from natural language de- scriptions

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.341968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.530258Z digest=sha256:17419203f1a5ad7f9cd3c70c05b4a2398ae5d48936aa0763c6017a0fc7559209

Observation 236d8990-d1f1-4111-9878-2464ddd35ffb · outbound

This paper cites At- tribute recognition by joint recurrent learning of context and correlation.

Recognizing Part Attributes with Insufficient Data At- tribute recognition by joint recurrent learning of context and correlation

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.316482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.535674Z digest=sha256:f7dc539babe9248d9aa162d7af1af85e572e2190792c8f4ad9be287cdde39402

Observation e65d7be1-5158-4227-a619-776acc1bdd30 · outbound

This paper cites Non-local neural networks.

Recognizing Part Attributes with Insufficient Data Non-local neural networks

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-14T14:21:44.542230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:21:44.542230Z digest=sha256:370a4648711ef70fc09a1c902d78e17708c1e3428ba725d1a546dfd1122e5744

Observation 5b334ffe-9c84-499e-b915-7f3fb3d3678f · outbound

This paper cites Cbam: Convolutional block attention module.

Recognizing Part Attributes with Insufficient Data Cbam: Convolutional block attention module

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.277380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.549973Z digest=sha256:ce86519de074741815d30900a50ff6d305ae210d576f77beed2570e72d11b72f

Observation d8a9e18d-f695-4d7e-8699-61d3514f93da · outbound

This paper cites Zero-Shot Learning -- The Good, the Bad and the Ugly.

Recognizing Part Attributes with Insufficient Data Zero-Shot Learning -- The Good, the Bad and the Ugly

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-14T14:21:44.556673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:21:44.556673Z digest=sha256:bc7d0720a116459cf4298e7d65400a402fa442b0405a191fc2b6ed073313e103

Observation 27372aed-7028-487c-a923-12622d62c25c · outbound

This paper cites Aggregated residual transformations for deep neural networks.

Recognizing Part Attributes with Insufficient Data Aggregated residual transformations for deep neural networks

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.253527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.563901Z digest=sha256:1a12593e33b55f969263f0c2b896f5a4c640d19fcd921bb41db429697fa6df5d

Observation fca324f6-34d1-44a7-a650-ebd3e6dd408c · outbound

This paper cites Show, attend and tell: Neural image caption gen- eration with visual attention.

Recognizing Part Attributes with Insufficient Data Show, attend and tell: Neural image caption gen- eration with visual attention

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-14T14:21:44.570924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:21:44.570924Z digest=sha256:68bc70795b8ba12bec59b1b535426da1d1af4023360f5b05bf9999cf36acd0c0

Observation 27ac3dbb-4b7d-4491-bc13-5b81e786b9ab · outbound

This paper cites A large-scale car dataset for fine-grained categorization and verification.

Recognizing Part Attributes with Insufficient Data A large-scale car dataset for fine-grained categorization and verification

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.208255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.577296Z digest=sha256:e8750e9ef993af4176359ce654848914541644a278b7f25e1c3d5bb99be45c08

Observation 4672dfbe-dcee-4af7-ae33-5e40fde77102 · outbound

This paper cites Part-based r-cnns for fine-grained category detection.

Recognizing Part Attributes with Insufficient Data Part-based r-cnns for fine-grained category detection

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.177960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.584692Z digest=sha256:3a2bcc2ebf8786842d18f60e434aab7061880b67bad3c4fe5d81cedd1acaa31d

Observation 80568aa9-0a99-4b1d-91b1-179ed7ebd8ed · outbound

This paper cites Deformable part descriptors for fine-grained recognition and attribute prediction.

Recognizing Part Attributes with Insufficient Data Deformable part descriptors for fine-grained recognition and attribute prediction

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.148933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.590733Z digest=sha256:412282de7454771586f0270688e8461623ebfadaeed7b46cf54ead67e697459f

Observation 37641f2b-a6f4-478d-9fbe-5c903b41f789 · outbound

This paper cites Panda: Pose aligned net- works for deep attribute modeling.

Recognizing Part Attributes with Insufficient Data Panda: Pose aligned net- works for deep attribute modeling

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.111848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.597891Z digest=sha256:8fc72786de728284d38c669bcb5e0a52b88b5dc6dac8f66a8b09c293cdee1db4

Observation bce582ef-670c-4e04-91de-32f799c9acd2 · outbound

This paper cites Zero-shot recog- nition via structured prediction.

Recognizing Part Attributes with Insufficient Data Zero-shot recog- nition via structured prediction

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.087611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.603963Z digest=sha256:c57d42d9c58e6da2393e2933760e4eb3e4595dfa7590a7f8207501b2ae624b0c

Observation d35d75dd-fc0c-4ed7-acac-0bce5bf4be49 · outbound

This paper cites A Large-scale Attribute Dataset for Zero-shot Learning.

Recognizing Part Attributes with Insufficient Data A Large-scale Attribute Dataset for Zero-shot Learning

Reference 66

Resolution
verified exact
local_arxiv, observed 2026-08-14T14:21:44.729906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.612675Z digest=sha256:37cd37288772d2c6c5beab5c6d2340b60c66402df7a662c5b6e874abbf8f7c34

Observation 1c5ce3b5-4d92-4e19-af96-5d0226d8f495 · outbound

This paper cites A modulation module for multi-task learning with applications in image retrieval.

Recognizing Part Attributes with Insufficient Data A modulation module for multi-task learning with applications in image retrieval

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.060945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.618411Z digest=sha256:5e106e7d26c4fc2444d8af62250a50bfd48264c74a0bb973b463ded8ec1c2a3b

Observation 299ab283-711e-4ee9-8f86-e43cbff45158 · outbound

This paper cites Pseudo mask augmented object detection.

Recognizing Part Attributes with Insufficient Data Pseudo mask augmented object detection

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:45.031328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.626025Z digest=sha256:55778880063abf158f46d53d58daf0e558a0f4f03690e27f8dab4d2d686c2456

Observation 7fc14a36-0714-4f1f-a24b-3d9668cf9879 · outbound

This paper cites Learning deep features for discrimi- native localization.

Recognizing Part Attributes with Insufficient Data Learning deep features for discrimi- native localization

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:44.993817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.633761Z digest=sha256:0226e568a0a64a04228bfb694cdda99155346607ceb3217bb2c87261ffa5d3df

Observation 425a9433-99ab-4816-a2e5-a27532bddf72 · outbound

This paper cites Pedestrian attribute classification in surveillance: Database and evaluation.

Recognizing Part Attributes with Insufficient Data Pedestrian attribute classification in surveillance: Database and evaluation

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:21:44.966507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-14T14:21:44.640182Z digest=sha256:bfd326005488540f387cd08f434faf7e019f34527daf66897a830e6d2e794b09

Pith citing papers

No inbound Pith citation observations are available.