Paper Citation Record · LEDGER

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

As of 22 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 1 inbound Pith citation observation for arXiv:1908.01998.

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

pith.paper-citation-record.v1
1908.01998 v4

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

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measured 66 of 66 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:28:59.706067Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T14:29:04.301590Z

Reference resolution

65 of 65 outbound references displayed

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External citation measurements

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Outbound references

Observation 0a60cf0a-9ba9-4db6-9f01-094d94b1ee04 · outbound

This paper cites Prototypical networks for few-shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Prototypical networks for few-shot learning

Reference 1

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Observation d68ea01c-12ce-46d0-b21f-5137ec1c91f7 · outbound

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

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Optimization as a model for few-shot learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.951352Z

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Observation c7ef8632-0b61-493c-a40d-eeb3a40dd317 · outbound

This paper cites Meta-learning with memory-augmented neural networks.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Meta-learning with memory-augmented neural networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.939537Z

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Observation 56df83ef-f3ae-48a9-ae04-75d0a7df08bf · outbound

This paper cites Matching networks for one shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Matching networks for one shot learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.926790Z

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Observation 48132b7b-9e95-4c40-9c78-684e04cfe120 · outbound

This paper cites Memory matching networks for one-shot image recog- nition.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Memory matching networks for one-shot image recog- nition

Reference 6

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Observation b82c165a-4bfd-4f02-84e9-d1b0f222c7c9 · outbound

This paper cites Dynamic few-shot visual learning without forgetting.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Dynamic few-shot visual learning without forgetting

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.882576Z

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Observation 00689331-ca46-4300-9a04-15e5ec20979c · outbound

This paper cites Learning to compare: Re- lation network for few-shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Learning to compare: Re- lation network for few-shot learning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.867557Z

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Observation 545fd3d0-229d-471f-b0db-c51769545fd8 · outbound

This paper cites Lstd: A low-shot transfer detector for object detection.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Lstd: A low-shot transfer detector for object detection

Reference 9

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Observation 61d34d34-8732-4fd6-bb92-074daabc4659 · outbound

This paper cites Few-shot object detection via feature reweighting.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Few-shot object detection via feature reweighting

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.838771Z

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Observation 4a127b39-87e8-4f44-9c38-2113b6b2f51f · outbound

This paper cites Repmet: Representative-based metric learning for classiﬁcation and few-shot object detection.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Repmet: Representative-based metric learning for classiﬁcation and few-shot object detection

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.824408Z

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Observation dd4fdb05-c3f8-4b2c-a3fa-d0cabef94f76 · outbound

This paper cites Meta r-cnn : Towards general solver for instance-level low-shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Meta r-cnn : Towards general solver for instance-level low-shot learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.810294Z

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Observation 1b7a8d65-b612-4949-b518-f61927730065 · outbound

This paper cites Microsoft coco: Common objects in context.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Microsoft coco: Common objects in context

Reference 13

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Observation 10df7d78-bc81-4329-a481-0531d7edcddc · outbound

This paper cites Histograms of oriented gra- dients for human detection.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Histograms of oriented gra- dients for human detection

Reference 14

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Observation 2cac2a1d-1392-4bc2-bcae-2251fd0e5ee2 · outbound

This paper cites Object detection with discriminatively trained part-based models.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Object detection with discriminatively trained part-based models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.773921Z

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Observation c8224800-fc84-4002-bcf0-284f662164ba · outbound

This paper cites Rapid object detection using a boosted cascade of simple features.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Rapid object detection using a boosted cascade of simple features

Reference 16

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Observation a0393746-21d1-4721-b95a-27f86b9358c8 · outbound

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

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Imagenet classiﬁcation with deep convolutional neural net- works

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.746282Z

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Observation 3ed8bba9-ec6b-419a-af8e-8e75a707f65a · outbound

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

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector You only look once: Uniﬁed, real-time object de- tection

Reference 18

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Observation c510c14d-09b3-4346-94c0-ca389175335f · outbound

This paper cites Yolo9000: better, faster, stronger.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Yolo9000: better, faster, stronger

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.723671Z

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Observation 65f55086-9109-43fe-94f1-741205d5d3e0 · outbound

This paper cites Ssd: Single shot multibox detector.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Ssd: Single shot multibox detector

Reference 20

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Observation c42234f7-c914-4051-822b-be2b7810531b · outbound

This paper cites Focal loss for dense object detection.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Focal loss for dense object detection

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.693460Z

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Observation f27d1d52-8eee-4903-adb7-fbfd223734b5 · outbound

This paper cites Receptive ﬁeld block net for accurate and fast object detection.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Receptive ﬁeld block net for accurate and fast object detection

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.674940Z

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Observation a2be9495-1cf7-4ef3-9207-e6468182b997 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Rich feature hierarchies for accurate object detection and semantic segmentation

Reference 23

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Observation 4b68eceb-6ec9-4256-a47c-cb34912469a6 · outbound

This paper cites Fast r-cnn.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Fast r-cnn

Reference 24

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Observation 2f9e1b26-343b-46cd-88c9-d8f5f43923ad · outbound

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

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 25

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Observation f342ad14-cafb-467c-a834-3cf4b97d3e67 · outbound

This paper cites Mask r-cnn.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Mask r-cnn

Reference 26

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Observation 5ffa9e93-f971-4b0f-8686-dfb03488f108 · outbound

This paper cites Sniper: Efﬁcient multi-scale training.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Sniper: Efﬁcient multi-scale training

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.625475Z

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Observation 067bc050-e0fb-41e1-9678-1fdcac1ed80a · outbound

This paper cites Is learning the n-th thing any easier than learning the ﬁrst? In NeurIPS, 1996.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Is learning the n-th thing any easier than learning the ﬁrst? In NeurIPS, 1996

Reference 28

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Observation df94f5ce-f0e4-4dac-b4f2-95bc147edf52 · outbound

This paper cites One-shot learning of object categories.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector One-shot learning of object categories

Reference 29

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Observation 32802188-b444-445e-8345-f6254608f715 · outbound

This paper cites One shot learning of simple visual con- cepts.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector One shot learning of simple visual con- cepts

Reference 30

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Observation 135ea27c-b5b2-4214-b370-346909a10755 · outbound

This paper cites One-shot learning by inverting a compositional causal process.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector One-shot learning by inverting a compositional causal process

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.566681Z

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Observation 5c7913c8-7707-41c5-8a8b-109f7014a29f · outbound

This paper cites Human-level concept learning through proba- bilistic program induction.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Human-level concept learning through proba- bilistic program induction

Reference 32

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Observation b22013c1-d2c5-4969-b7bb-00d1bf3b9acc · outbound

This paper cites One shot learning via com- positions of meaningful patches.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector One shot learning via com- positions of meaningful patches

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.539437Z

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Observation 5710ab79-d388-4fba-a106-74420007a8e9 · outbound

This paper cites Tadam: Task dependent adaptive metric for improved few-shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Tadam: Task dependent adaptive metric for improved few-shot learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.527391Z

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Observation c44778f0-e858-44db-a1ac-a46bf75250e3 · outbound

This paper cites Few-shot learning through an information retrieval lens.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Few-shot learning through an information retrieval lens

Reference 35

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Observation 8af2f7fb-c9a6-4d1d-9e2a-74b76210a3a9 · outbound

This paper cites Low-shot visual recognition by shrinking and hallucinating features.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Low-shot visual recognition by shrinking and hallucinating features

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.501832Z

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Observation 7847c676-0d4e-4157-b6a0-0282fbf010ea · outbound

This paper cites Siamese neural networks for one-shot image recognition.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Siamese neural networks for one-shot image recognition

Reference 37

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Observation d405fb81-5a0c-4e2e-acb9-c661179b22a0 · outbound

This paper cites Meta networks.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Meta networks

Reference 38

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This paper cites Rapid adaptation with conditionally shifted neurons.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Rapid adaptation with conditionally shifted neurons

Reference 39

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Observation 90bcec03-0560-46d2-af21-894dc0199521 · outbound

This paper cites Low-shot learning from imaginary data.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Low-shot learning from imaginary data

Reference 40

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Observation 068f8bbe-5bb1-4965-bb10-475bcab6ec01 · outbound

This paper cites Revisiting local descriptor based image-to-class measure for few-shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Revisiting local descriptor based image-to-class measure for few-shot learning

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.446073Z

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Observation cd1eed3e-4ce6-417e-b11d-18c9d8186d2f · outbound

This paper cites Dense classiﬁcation and implanting for few-shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Dense classiﬁcation and implanting for few-shot learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.434480Z

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Observation 09050c6f-3c75-4434-8402-3c97d6611887 · outbound

This paper cites Yoo Jongmin Kim, Taesup Kim.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Yoo Jongmin Kim, Taesup Kim

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.421844Z

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Observation f252bf9c-8f5b-403a-9214-097c93517301 · outbound

This paper cites Generating classiﬁ- cation weights with gnn denoising autoencoders for few-shot learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Generating classiﬁ- cation weights with gnn denoising autoencoders for few-shot learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.408005Z

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Observation 7d83959d-5c63-4fd9-a8cc-9aae51d77391 · outbound

This paper cites Finding task-relevant features for few- shot learning by category traversal.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Finding task-relevant features for few- shot learning by category traversal

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.393812Z

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Observation f44af0b3-b3eb-44d0-8c25-249f217e7004 · outbound

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

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Model- agnostic meta-learning for fast adaptation of deep networks

Reference 46

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This paper cites Few-shot semantic segmen- tation with prototype learning.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Few-shot semantic segmen- tation with prototype learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.377792Z

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Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Unresolved cited work

Reference 48

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Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Unresolved cited work

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Observation 66509848-5a9c-4b1c-87a5-fa25163223a1 · outbound

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Reference 50

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Observation c5a76312-4d50-4970-9602-96de15e9b886 · outbound

This paper cites Few-example object detection with model communi- cation.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Few-example object detection with model communi- cation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.317821Z

Source-reported events for the cited work

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Observation f0e32e60-8923-46e6-b2d6-0c6a49654773 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.027657Z

Source-reported events for the cited work

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Observation ee215f2f-047e-4fc8-a28f-dd2a089ffaec · outbound

This paper cites The pascal visual object classes (voc) challenge.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector The pascal visual object classes (voc) challenge

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.031764Z

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Observation 9d8a8462-52db-4625-aee1-20ca3172be55 · outbound

This paper cites The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.035817Z

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Observation a5ee3c6f-5fa5-4f4e-8758-1932d65acf0a · outbound

This paper cites Visual genome: Connecting language and vision using crowdsourced dense image annotations.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Visual genome: Connecting language and vision using crowdsourced dense image annotations

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.039567Z

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Unavailable: canonical work link unavailable.

Observation 9d0df6a1-3dbb-493a-bd63-5cca31495202 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Imagenet: A large-scale hierarchical image database

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.043356Z

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Unavailable: canonical work link unavailable.

Observation 18de1939-68e4-426d-bf95-4e2e4a49b6f4 · outbound

This paper cites Wordnet: a lexical database for english.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Wordnet: a lexical database for english

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.046715Z

Source-reported events for the cited work

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Observation 979dfdbd-7d54-43a4-bbd7-6b7b1a74a9f0 · outbound

This paper cites Fully-convolutional siamese networks for object tracking.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Fully-convolutional siamese networks for object tracking

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.263396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2d5830be-7f44-457b-860f-0b7f87819e80 · outbound

This paper cites Class-agnostic counting.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Class-agnostic counting

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.251240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 25732357-bec4-40f2-8535-9eb48ebc7b3c · outbound

This paper cites Siamrpn++: Evolution of siamese visual tracking with very deep networks.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Siamrpn++: Evolution of siamese visual tracking with very deep networks

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.237179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4addc90d-b1f4-421e-a23f-2dfeccaa1074 · outbound

This paper cites Rep- met: Representative-based metric learning for classiﬁcation and one-shot object detection.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Rep- met: Representative-based metric learning for classiﬁcation and one-shot object detection

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.220311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 686b9ec7-8462-47c5-ba52-0bd8b0211909 · outbound

This paper cites Selective search for ob- ject recognition.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Selective search for ob- ject recognition

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.205714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c3e4dd33-e16b-4dc4-97de-f82d18f7eca4 · outbound

This paper cites an unresolved cited work.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-14T15:04:07.189209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ec8681db-8a28-41ca-b6ac-2205823e90ac · outbound

This paper cites Arteta, V.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Arteta, V

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T15:04:07.175343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d5f15c1f-0b27-428c-8af6-cf679d067ec7 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector The cityscapes dataset for semantic urban scene understanding

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.081374Z

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Unavailable: canonical work link unavailable.

Observation 876f13b5-fcb3-4e12-9839-48ff549fe349 · outbound

This paper cites Domain adaptive faster r-cnn for object de- tection in the wild.

Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector Domain adaptive faster r-cnn for object de- tection in the wild

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-14T15:04:07.086168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 77e7c96d-dcb4-4545-be38-5fdcac5e5906 · inbound

Deep Learning in Automated Power Line Inspection: A Review cites this paper.

Deep Learning in Automated Power Line Inspection: A Review Few-Shot Object Detection with Attention-RPN and Multi-Relation Detector

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-08-08T14:29:04.308537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.