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

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.586541Z

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.536364Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.503316Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.467671Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.445276Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.425759Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.407749Z

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.390872Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.371984Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:50.904719Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.343228Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.326396Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.309265Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.291120Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.272993Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.254331Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.237448Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.220205Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.202248Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:50.958154Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.173494Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.156684Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.139925Z

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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: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.123752Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.108579Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.090768Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.073206Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.056721Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:51.007780Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:51.013140Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.039214Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:52.022052Z

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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

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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

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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

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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

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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

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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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+00:00.

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.

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 2026-08-23T06:30:58.430688+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers