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Paper Citation Record · LEDGER

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection

As of 19 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2505.16442.

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

pith.paper-citation-record.v1
2505.16442 v1

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:04:51.246063Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

72 of 72 outbound references displayed

  • verified exact1
  • verified fuzzy64
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81c181de-e77d-4355-8399-91b62eb6ec3c · outbound

This paper cites Attentive alignment network for multispectral pedestrian detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Attentive alignment network for multispectral pedestrian detection,

Reference 1

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Source-reported events for the cited work

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Observation 27fb4a33-6e8f-4110-9324-13dcfaeb4a0a · outbound

This paper cites To- wards large-scale small object detection: Survey and benchmarks,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection To- wards large-scale small object detection: Survey and benchmarks,

Reference 2

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no resolver link, observed 2026-08-07T15:04:50.848032Z

Source-reported events for the cited work

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Observation 262de464-8ab8-4e3d-bfb2-0cbf70bcc751 · outbound

This paper cites Scale match for tiny person detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Scale match for tiny person detection,

Reference 3

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Source-reported events for the cited work

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Observation 08fa8729-04ce-4176-bd78-e6825e260c66 · outbound

This paper cites Rfla: Gaussian receptive field based label assignment for tiny object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Rfla: Gaussian receptive field based label assignment for tiny object detection,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 7f9f8626-5443-4a99-a69a-92916003c6bc · outbound

This paper cites Visdrone-det2021: The vision meets drone object detection challenge results,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Visdrone-det2021: The vision meets drone object detection challenge results,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5f0a9e94-71ed-4e30-a0db-9f1e2fe1532d · outbound

This paper cites Accurate and robust object detection via selective adversarial learning with constraints,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Accurate and robust object detection via selective adversarial learning with constraints,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ecc1adfd-150d-4524-848c-7867124245d3 · outbound

This paper cites Infrared small target detection with scale and location sensitivity,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Infrared small target detection with scale and location sensitivity,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation bfa1354b-bf19-4004-8820-344d43852623 · outbound

This paper cites Sliding window detection and distance-based matching for tracking on gigapixel images,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Sliding window detection and distance-based matching for tracking on gigapixel images,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:50.884000Z digest=sha256:10ced358b26eaae5e3cdaeff256678a76a23ffde6de26183e357284d37b7b528

Observation c0cfa74a-6202-4498-951b-2a129ffe51e9 · outbound

This paper cites Object Detection in Autonomous Vehicles: Status and Open Challenges.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Object Detection in Autonomous Vehicles: Status and Open Challenges

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f19eb496-1851-464b-b63c-02f42d81fb6e · outbound

This paper cites Dot distance for tiny object detection in aerial images,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Dot distance for tiny object detection in aerial images,

Reference 10

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a387a0fe-9d5d-461d-a514-d3e19b3b06cf · outbound

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

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5304e8e1-8c01-4591-a3db-f65d6a0f3614 · outbound

This paper cites Cascade r-cnn: High quality object detection and instance segmentation,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Cascade r-cnn: High quality object detection and instance segmentation,

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ba0780fd-e6ea-4279-bd24-858cd5d29f63 · outbound

This paper cites Small object detection via coarse-to-fine proposal generation and imitation learning,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Small object detection via coarse-to-fine proposal generation and imitation learning,

Reference 13

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9d164fd5-174d-476b-b1d8-7a2c6db4a62a · outbound

This paper cites S3fd: Single shot scale-invariant face detector,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection S3fd: Single shot scale-invariant face detector,

Reference 14

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raw_fallback, observed 2026-08-07T15:04:52.326396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4238d6b5-89d3-40f6-8ce8-372146f368e9 · outbound

This paper cites Seeing small faces from robust anchor’s perspective,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Seeing small faces from robust anchor’s perspective,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 7c03e0c6-6159-4ecc-9aa9-311fbe7d5832 · outbound

This paper cites Scale-aware fast r-cnn for pedestrian detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Scale-aware fast r-cnn for pedestrian detection,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 1265a0b2-d92e-4d95-b1a0-1e87787e45c1 · outbound

This paper cites Feature pyramid networks for object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Feature pyramid networks for object detection,

Reference 17

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8be900ef-9e82-467d-b268-eb5a563f179c · outbound

This paper cites Querydet: Cascaded sparse query for accelerating high-resolution small object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Querydet: Cascaded sparse query for accelerating high-resolution small object detection,

Reference 18

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Observation f203ce82-5c21-4d95-9b35-2c361442b92b · outbound

This paper cites Finding tiny faces in the wild with generative adversarial network,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Finding tiny faces in the wild with generative adversarial network,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 15ddf8d8-5dde-4505-83ee-aa1d0621e167 · outbound

This paper cites Sod-mtgan: Small object detection via multi-task generative adversarial network,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Sod-mtgan: Small object detection via multi-task generative adversarial network,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 65ffd1c9-cdcf-4161-a236-9415192a3700 · outbound

This paper cites Better to follow, follow to be better: Towards precise supervision of feature super-resolution for small object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Better to follow, follow to be better: Towards precise supervision of feature super-resolution for small object detection,

Reference 21

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 8f48600d-e9c9-4641-934d-ff93faeabe23 · outbound

This paper cites Extended feature pyramid network for small object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Extended feature pyramid network for small object detection,

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:04:50.958154Z digest=sha256:95e3a1bc043fe5db5b405ffe8054cb0965523f369d4d25bdfd5502e59cacba66

Observation fe0eabfe-9c16-44e8-a0cc-6d2d352002e0 · outbound

This paper cites Path aggregation network for instance segmentation,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Path aggregation network for instance segmentation,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation e8cdb940-830f-4f32-b052-ac993452790d · outbound

This paper cites M2det: A single-shot object detector based on multi-level feature pyramid network,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection M2det: A single-shot object detector based on multi-level feature pyramid network,

Reference 24

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raw_fallback, observed 2026-08-07T15:04:52.156684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:50.969489Z digest=sha256:6cb2b4754e2147335928539d148ea132d301e6f1c62234fda055461a967f6d40

Observation 6119cb98-e7b8-4d42-85b8-5a8fd632de3f · outbound

This paper cites Effective fusion factor in fpn for tiny object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Effective fusion factor in fpn for tiny object detection,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation ea87ddc7-59e8-4456-a373-401a3f253113 · outbound

This paper cites Self-mimic learning for small-scale pedestrian detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Self-mimic learning for small-scale pedestrian detection,

Reference 26

Resolution
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raw_fallback, observed 2026-08-07T15:04:52.123752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:50.980480Z digest=sha256:3a8576e92fdab866fffc8b06a1e5a6f06cc7e8f2e77c9590a6d7d736bd26e318

Observation 0ac1ea53-08e4-4459-80b6-7e6581616b06 · outbound

This paper cites Robust small-scale pedestrian detection with cued recall via memory learning,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Robust small-scale pedestrian detection with cued recall via memory learning,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:50.986721Z digest=sha256:93224904e2125f4665a10175392544916544ccb4f84596644988db63744ac316

Observation 7598ba61-01ae-4633-8557-41cea55b8035 · outbound

This paper cites Mlfa: Towards realistic test time adaptive object detection by multi-level feature alignment,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Mlfa: Towards realistic test time adaptive object detection by multi-level feature alignment,

Reference 28

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raw_fallback, observed 2026-08-07T15:04:52.090768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:50.992097Z digest=sha256:fe3f22aa5a1b1a46864e13e7ec34b5a01314e5249e3e8b33905e93d6b6e75006

Observation a8f9f378-8d00-4275-a46a-9d08161b6e34 · outbound

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

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Rich feature hierarchies for accurate object detection and semantic segmentation,

Reference 29

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raw_fallback, observed 2026-08-07T15:04:52.073206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:50.997313Z digest=sha256:ee3148798087cb39520deb471870d133021480faef63925f8c7818dd431a1dc5

Observation 3211c2cb-c7cd-4219-892c-45a8eb5fb6ea · outbound

This paper cites Centernet: Keypoint triplets for object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Centernet: Keypoint triplets for object detection,

Reference 30

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raw_fallback, observed 2026-08-07T15:04:52.056721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.002547Z digest=sha256:4395f363ac82127305b68da4afe80a9e5a2bebd6bbbdd83515ece5e1fb59a603

Observation f6c3692a-65c4-4a9e-812c-ed6dfb1e62c5 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:04:51.007780Z digest=sha256:c6e9dc9396017373bc7bf3ba87157e0f8fd04c1798d2cf8e94639dbc4dbcaedb

Observation 3c95e4f9-a963-48f6-8d74-4add20c15995 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection YOLOX: Exceeding YOLO Series in 2021

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:04:51.013140Z digest=sha256:4a13bcba8bb9396d8be269cd91a100f297bf2276683664b0729b930c474397a5

Observation 52ef6b55-58f2-48b7-aa7e-ac9337b8e50d · outbound

This paper cites Safnet: A semi-anchor-free network with enhanced feature pyramid for object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Safnet: A semi-anchor-free network with enhanced feature pyramid for object detection,

Reference 33

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raw_fallback, observed 2026-08-07T15:04:52.039214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.018917Z digest=sha256:1f66b0baf23ee73111628d620e95bb48e9ef5056f12228dc40ac5ea31fe60cf4

Observation 3d7442be-414a-4204-8b9d-0e12a32a9873 · outbound

This paper cites Siamese-detr for generic multi- object tracking,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Siamese-detr for generic multi- object tracking,

Reference 34

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raw_fallback, observed 2026-08-07T15:04:52.022052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.024555Z digest=sha256:a93e9574d842c14b8ab6fffbe1ee4643fa42949b8b1b92a835c5678d67d03785

Observation 66b1453e-5ad9-4136-b724-5d7325f8ee56 · outbound

This paper cites Frequency- aware feature fusion for dense image prediction,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Frequency- aware feature fusion for dense image prediction,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:52.004445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.030163Z digest=sha256:dcd14ec6d8a4b0502eb25365c637f9e24edb9a0246984323b04588fe9314eec7

Observation 1bfa1e00-6d37-433f-a5f1-8c0b81f0646e · outbound

This paper cites Stairnet: Top-down semantic aggregation for accurate one shot detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Stairnet: Top-down semantic aggregation for accurate one shot detection,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.986843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.035933Z digest=sha256:1c74956d662bc6529d43b9bbe2bbb9bd19863766da509ea226da74975385d43b

Observation 7cd7d8a4-9aff-4e5f-acbe-5a96d3bab59c · outbound

This paper cites Ipg-net: Image pyramid guidance network for small object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Ipg-net: Image pyramid guidance network for small object detection,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.968938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.041325Z digest=sha256:b6fe368cf98c2e2ee88eda7470b1adff21abb7ddc5288d1a0f90ddd34643ebed

Observation 56535f96-a5fd-4a1c-b5d8-0b20db731710 · outbound

This paper cites Centralized feature pyramid for object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Centralized feature pyramid for object detection,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.950816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.046455Z digest=sha256:247e94b795f11f0510728f667af6681a7a76cc4de773984d2150cbcbe64f313f

Observation dfc105f3-f65e-4918-ba43-c6517a7e7e89 · outbound

This paper cites Perceptual generative adversarial networks for small object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Perceptual generative adversarial networks for small object detection,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.931973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.052108Z digest=sha256:1300d29b1c1dbc9792db1681c619bfb0488c7d25a7e505958bdd0d975220639e

Observation 4939a34c-3b11-4ac4-bff0-2abdd223e939 · outbound

This paper cites Mega: molecular evolutionary genetics analysis software for microcomputers,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Mega: molecular evolutionary genetics analysis software for microcomputers,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.913530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.057760Z digest=sha256:edf86c06df1ae276d71f5ab567ead62d9f4f64854bfb4b1ed1678973fe31459a

Observation ae59d4f7-a805-4639-a0c6-a796725aefb5 · outbound

This paper cites Mcibi++: Soft mining contextual information beyond image for semantic segmentation,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Mcibi++: Soft mining contextual information beyond image for semantic segmentation,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.895193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.063735Z digest=sha256:3b7919b52df87d173ef3da63aa2d2de78da6a4748e642fd9af511e4a74fb5467

Observation de300b47-cfea-41af-9617-9b4faa93da76 · outbound

This paper cites Mne software for processing meg and eeg data,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Mne software for processing meg and eeg data,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.877133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.068934Z digest=sha256:7cb124f77eab1b5d56852997e4f5d9218e785bff1ee09b10215cb32649523122

Observation 06f8d082-3db0-4a2a-bec0-df4f8d788a9b · outbound

This paper cites Cross-batch memory for embedding learning,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Cross-batch memory for embedding learning,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.859216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.074779Z digest=sha256:fa99d41bb0a75d228aeb2d210746fd844c490513e435205c14de9bc7a06b145f

Observation baef777a-16e3-4619-9efd-00a06a0721cc · outbound

This paper cites Memory enhanced global- local aggregation for video object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Memory enhanced global- local aggregation for video object detection,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.842386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.079732Z digest=sha256:04e4d1cb2e10c3407b20ee2b5c66e37c5fd3fdc6e72a530dcae4d55985617d3f

Observation 4c18147f-1155-49cb-a058-78bcbe048d16 · outbound

This paper cites Invariance matters: Exemplar memory for domain adaptive person re-identification,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Invariance matters: Exemplar memory for domain adaptive person re-identification,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.824628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.085020Z digest=sha256:98b2efd7745d5ced2a5b506bdcaf34f310d02124e2d42ad746b72fc847fcb48a

Observation 74b10f4d-9776-4f9e-80ff-3b39965f7bfa · outbound

This paper cites Memory-based neigh- bourhood embedding for visual recognition,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Memory-based neigh- bourhood embedding for visual recognition,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.808450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.091035Z digest=sha256:c4f4f6fcb1faf3f4ba65f7247a923cbba3616d0e6d7accb050d6fe7bb9d5ab6f

Observation ed86df59-dae7-47c8-b73b-a1976820b5db · outbound

This paper cites Long-term feature banks for detailed video understanding,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Long-term feature banks for detailed video understanding,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.791027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.097037Z digest=sha256:94669973cb826c90503e206ff9375a545fde5228066ebe7c94456c830633e67f

Observation 51161a15-2531-48ae-b5aa-49f9f4134624 · outbound

This paper cites Object detection difficulty: Suppressing over-aggregation for faster and better video object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Object detection difficulty: Suppressing over-aggregation for faster and better video object detection,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.773721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.103979Z digest=sha256:e6eaa5f4f992e3b81f6ff76cda7b6e4708c7c8814cc005217a3e2189c370724d

Observation 12ea6c22-f091-49c3-8e14-db84bc317be2 · outbound

This paper cites Transformer based pluralistic image completion with reduced information loss,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Transformer based pluralistic image completion with reduced information loss,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.757428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.109893Z digest=sha256:790b66b62306ea129a010f89e01800c0098f208a2e176cde48730b73ab4712f7

Observation 9ba3ae7a-7db0-4c52-b1bf-0b3d65550835 · outbound

This paper cites Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.740507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.116568Z digest=sha256:3fcbdc002a21cc54f9d8e946e49bc3725a9cf17eb6d4732316fd6ade45878284

Observation 9a1c0ae1-368d-449a-9539-76eee4dd4af3 · outbound

This paper cites Fast r-cnn,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Fast r-cnn,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.722501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.122906Z digest=sha256:ce21bcf9855e3af899cedf3bfa6d3ab8e38323755631c95dadafd07e8bb27307

Observation 83eb2f3b-c4d3-40dc-9aa5-60386598a9c9 · outbound

This paper cites Crossvit: Cross-attention multi- scale vision transformer for image classification,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Crossvit: Cross-attention multi- scale vision transformer for image classification,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.705084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.132304Z digest=sha256:ee145558db5eae44a7b3cd6d45dabd941eb2bc1e58fd3b65c17b9efddc9dc568

Observation 020eea91-d710-4092-83e9-74a36a235a3b · outbound

This paper cites Cornernet: Detecting objects as paired keypoints,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Cornernet: Detecting objects as paired keypoints,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.686104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.138400Z digest=sha256:f8933bf17885bd84c8f2a35d579d29fa4fec83d0009696aad508f47710090828

Observation aee92227-4984-48d3-bedf-cc498519ce48 · outbound

This paper cites Deep residual learning for image recognition,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Deep residual learning for image recognition,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.669699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.143630Z digest=sha256:6a7cc05ec02daff9421e2c390a5550fda073e5f415aed049dc6c20f3b729a907

Observation 737479b5-9a2b-4464-a14f-1245a02db1f1 · outbound

This paper cites Reppoints: Point set representation for object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Reppoints: Point set representation for object detection,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.653811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.149305Z digest=sha256:5b62771792f5fa8e03b4e5c184f08e05045b349808e87dbaff3acc9bddfd63d4

Observation af9182b3-cb0e-4aa7-b116-84a257f7798a · outbound

This paper cites Sparse r-cnn: End-to-end object detection with learnable proposals,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Sparse r-cnn: End-to-end object detection with learnable proposals,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.636142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.154634Z digest=sha256:63c0744b1c423e8e1499111b09d3d495abc6e891581c30ae6a4b8868de5c1fcf

Observation 2b17bec7-76e2-4e32-badb-ced716fd9b3e · outbound

This paper cites Detrs beat yolos on real-time object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Detrs beat yolos on real-time object detection,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.617558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.159639Z digest=sha256:37ac72b0206ae04844183a233ec2b8048734727df1b48cc639b83a283233c5ab

Observation 37b47066-f7eb-4097-a622-96c8c18fb857 · outbound

This paper cites Focal loss for dense object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Focal loss for dense object detection,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.598272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.164583Z digest=sha256:6fc7ad6170173c908bbfa0010b81a78afbf32a44b4516dbb155907fe9699b77b

Observation e44a2fce-75e2-4a13-b94b-daf0bbfc77ea · outbound

This paper cites Fcos: Fully convolutional one- stage object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Fcos: Fully convolutional one- stage object detection,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.579637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.170671Z digest=sha256:9985cb5d8b7800961470f3c3a8345a257ffedf42b87f4b10d34e481e8c467ff3

Observation 94bbe47a-0839-4255-b6ec-e5327f0a71de · outbound

This paper cites Dynamic head: Unifying object detection heads with attentions,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Dynamic head: Unifying object detection heads with attentions,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.560425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.176242Z digest=sha256:ad54ae22af19cb8c0b13fa8815a663811519d7210aa8d71862e2e5674014b6cf

Observation 31237636-b84d-4c0b-b752-5eb463cdf5ff · outbound

This paper cites Cascade rpn: Delving into high-quality region proposal network with adaptive convolution,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Cascade rpn: Delving into high-quality region proposal network with adaptive convolution,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.542024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.182054Z digest=sha256:104f007da4b836cfb9d015c2908dae56c10179d7b09d63a9ddbd7d5ba73da83a

Observation a9b91be1-dd05-497d-807c-6a4d7f81bbe2 · outbound

This paper cites Kldet: Detecting tiny objects in remote sensing im- ages via kullback-leibler divergence,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Kldet: Detecting tiny objects in remote sensing im- ages via kullback-leibler divergence,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.525243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.187882Z digest=sha256:1a9be432f2627b5ee06f6295f5550622bab0da33707f10ead05c9cd74d0452d7

Observation 2cc5ea8f-6776-4d9f-b7f8-1930c68f0c6d · outbound

This paper cites Align deep features for oriented object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Align deep features for oriented object detection,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.508151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.193407Z digest=sha256:bd015973fcf49cbc438d369854040de7c52fb017ac27e010fa963096d7f4dabe

Observation 0bf2c249-faea-4dd8-9f3a-ce2d4f5dc79f · outbound

This paper cites Oriented reppoints for aerial object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Oriented reppoints for aerial object detection,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.490016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.199385Z digest=sha256:f434cbd107a7904dc427f9712bc6ffa69507cfb8805e4541a9a55df19dc9d707

Observation 370d494f-e000-4586-8e11-faf733090096 · outbound

This paper cites Multi-oriented object detection in aerial im- ages with double horizontal rectangles,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Multi-oriented object detection in aerial im- ages with double horizontal rectangles,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.471110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.204658Z digest=sha256:3e14d5e68d41957e8b9adc7ecaf86c0b1ded17ba6a5dca204ef260f8301d245a

Observation 6b0973f1-fbdc-4611-8441-3273397608f7 · outbound

This paper cites Gliding vertex on the horizontal bounding box for multi-oriented object detection,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Gliding vertex on the horizontal bounding box for multi-oriented object detection,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.453017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.209805Z digest=sha256:650f5fc0d8047a7dbdae7be27bfdc5b0708a9e7deef7bd539eb5172b1642fb0a

Observation 52e2db89-e54c-4bdf-95d0-06b5bfbda644 · outbound

This paper cites Oriented r-cnn and beyond,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Oriented r-cnn and beyond,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.434557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.216243Z digest=sha256:45f05c070552bf397d2739fb14d51acb2f2a79a28ae4bf47236c0ead2f83103d

Observation 291b4c58-b8cb-4e50-a6ae-725665c6a711 · outbound

This paper cites Dual-aligned oriented detector,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Dual-aligned oriented detector,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.414807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.222069Z digest=sha256:399c0e236d2d4131db9217e2c7a1956e6078bde0903214f0e38680dfb874690d

Observation c5f936ec-9a4c-4468-81e2-c16796dfe745 · outbound

This paper cites LSKNet: A Foundation Lightweight Backbone for Remote Sensing.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection LSKNet: A Foundation Lightweight Backbone for Remote Sensing

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:04:51.294319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.228125Z digest=sha256:99676d32a4e7c3461a903aae69c4ca997e30a8e0813b80c3a1d47ab39a7f1ecc

Observation 36999208-53e2-4676-98a0-c920934aa94d · outbound

This paper cites Dota: A large-scale dataset for object detection in aerial images,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Dota: A large-scale dataset for object detection in aerial images,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.395766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.234282Z digest=sha256:3425fd66f492d8072d9068a11455f24a7da42b4ddcf3bb660d87352d0cd8aac8

Observation 95f50d0f-0b90-4bfe-8ba9-a8cf304d796d · outbound

This paper cites Microsoft coco: Common objects in context,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection Microsoft coco: Common objects in context,

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T15:04:51.240954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:04:51.240954Z digest=sha256:12de3602871134c632bd5953a14508f369e90004c4eb1d267f3676d70dfcbb51

Observation 854d7279-e63c-46a7-a0a8-431f91537783 · outbound

This paper cites End-to-end object detection with transformers,.

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection End-to-end object detection with transformers,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:51.366206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T15:04:51.246063Z digest=sha256:1426d5766f0530e957d3b382586e5e1779824247b83b130de850c1127e0b7118

Pith citing papers

No inbound Pith citation observations are available.