Count Anything | Paper Citation Record

Observation 73248dd2-901e-4f40-ad0f-fd85cb03a06e · outbound

This paper cites Foundation models defining a new era in vision: A survey and outlook.IEEE Trans.

Count Anything Foundation models defining a new era in vision: A survey and outlook.IEEE Trans

Reference 1

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Observation 10512b7e-d9c7-4bc0-b955-99280e73f8bc · outbound

This paper cites Vision foundation models in remote sensing: A survey.IEEE Geosci.

Count Anything Vision foundation models in remote sensing: A survey.IEEE Geosci

Reference 2

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Observation 4ea42d82-df68-432a-891f-ff8252dc7af2 · outbound

This paper cites Florence: A New Foundation Model for Computer Vision.

Count Anything Florence: A New Foundation Model for Computer Vision

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-06-28T23:02:46.008216Z

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Observation 01c9a90a-8d45-4ff1-a909-6b456130d444 · outbound

This paper cites VLCounter: Text-aware visual representa- tion for zero-shot object counting.

Count Anything VLCounter: Text-aware visual representa- tion for zero-shot object counting

Reference 4

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Observation 20c458c8-8055-48bc-bd42-2955734d5bc7 · outbound

This paper cites Zero-Shot Object Counting With Good Exemplars.

Count Anything Zero-Shot Object Counting With Good Exemplars

Reference 5

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Observation 397cc9fe-75a6-4798-ad28-f642806aecc7 · outbound

This paper cites CountGD: Multi-modal open-world counting.

Count Anything CountGD: Multi-modal open-world counting

Reference 6

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Observation c1cbcbdb-d25b-4222-a971-874860292aab · outbound

This paper cites CountGD++: Generalized prompting for open-world counting.

Count Anything CountGD++: Generalized prompting for open-world counting

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 49817d3c-4e01-4dd4-b1c2-0ac0db384f0b · outbound

This paper cites Deep learning in crowd counting: A survey.CAAI Trans.

Count Anything Deep learning in crowd counting: A survey.CAAI Trans

Reference 8

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Observation 2771b7a9-bd77-430e-b918-20e6281c0652 · outbound

This paper cites Zero-shot object counting.

Count Anything Zero-shot object counting

Reference 9

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Observation 481abecf-4fd6-43bb-8207-dad07e18da89 · outbound

This paper cites Rethinking counting and localization in crowds: A purely point-based framework.

Count Anything Rethinking counting and localization in crowds: A purely point-based framework

Reference 10

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Observation 26939b3e-2fdf-4b76-b68f-adc708abefdc · outbound

This paper cites Learning To Count Anything: Reference-less class-agnostic counting with weak supervision.

Count Anything Learning To Count Anything: Reference-less class-agnostic counting with weak supervision

Reference 11

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Observation 23749e2d-ff83-4650-b73e-fb61f8a20ff3 · outbound

This paper cites Learning To Count Everything.

Count Anything Learning To Count Everything

Reference 12

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Observation 2d9123f4-7777-4c14-9478-0b9e5b916810 · outbound

This paper cites Few-shot Object Counting and Detection.

Count Anything Few-shot Object Counting and Detection

Reference 13

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Observation 7e18ec9c-f9d3-4719-b9cb-6847029b03d0 · outbound

This paper cites Single-image crowd counting via multi-column convolutional neural network.

Count Anything Single-image crowd counting via multi-column convolutional neural network

Reference 14

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Observation d2e1628b-87de-4ea7-a668-68259c23d33f · outbound

This paper cites Improving Point-Based Crowd Counting and Localization Based on Auxiliary Point Guidance.

Count Anything Improving Point-Based Crowd Counting and Localization Based on Auxiliary Point Guidance

Reference 15

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Observation 943feaec-b273-499a-9a14-cc090b34f742 · outbound

This paper cites CCTrans: Simplifying and Improving Crowd Counting with Transformer.

Count Anything CCTrans: Simplifying and Improving Crowd Counting with Transformer

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:02:45.997448Z

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Observation 45f5e7e5-0f51-4758-ab30-05134e8deaba · outbound

This paper cites Microsoft COCO: Common objects in context.

Count Anything Microsoft COCO: Common objects in context

Reference 17

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Observation a5c87510-71e8-4492-b84b-9c3c0ad95711 · outbound

This paper cites an unresolved cited work.

Count Anything Unresolved cited work

Reference 18

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Observation 76617ea3-6175-4fe9-9800-848d3efcd099 · outbound

This paper cites Sindagi, Rajeev Yasarla, and Vishal M.

Count Anything Sindagi, Rajeev Yasarla, and Vishal M

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation cad2ac65-a0bd-4981-aa0c-b8b23c7e6d7b · outbound

This paper cites NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.Sci.

Count Anything NuInsSeg: A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.Sci

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 1097ea59-66c1-4c66-a7fa-f223b8f02a8c · outbound

This paper cites A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology.IEEE Trans.

Count Anything A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology.IEEE Trans

Reference 21

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Observation 95778287-93f4-4fa9-bb8b-3b1932b79170 · outbound

This paper cites CellBinDB: A large-scale multimodal annotated dataset for cell segmentation with benchmarking of universal models.GigaScience, 14:giaf069, 2025.

Count Anything CellBinDB: A large-scale multimodal annotated dataset for cell segmentation with benchmarking of universal models.GigaScience, 14:giaf069, 2025

Reference 22

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Observation 38bd68f5-7273-4cbd-8415-1c769f6337f7 · outbound

This paper cites Objects365: A large-scale, high-quality dataset for object detection.

Count Anything Objects365: A large-scale, high-quality dataset for object detection

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 81e346db-c434-41bf-8fd0-fd2707a0d85b · outbound

This paper cites Detection and Tracking Meet Drones Challenge.IEEE Trans.

Count Anything Detection and Tracking Meet Drones Challenge.IEEE Trans

Reference 24

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Observation 8b61b330-4886-440a-89a5-ba70ce98e126 · outbound

This paper cites Ahmed Raza, Nasir M.

Count Anything Ahmed Raza, Nasir M

Reference 25

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Observation fb7d0e62-5fd9-47e0-9399-e931448acf10 · outbound

This paper cites Venkatesh Babu.

Count Anything Venkatesh Babu

Reference 26

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Observation 05aeb8db-6afe-4054-b911-1c01705590c7 · outbound

This paper cites an unresolved cited work.

Count Anything Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 541199bc-66c0-4707-87bc-90c8c43f6850 · outbound

This paper cites Distribution Matching for Crowd Counting.

Count Anything Distribution Matching for Crowd Counting

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 314b05a6-3b0b-4f47-b97e-a25eb0210b36 · outbound

This paper cites CLIP-Count: Towards text-guided zero-shot object counting.

Count Anything CLIP-Count: Towards text-guided zero-shot object counting

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation f75383a0-fbf2-4b4f-b333-95ba723d10b7 · outbound

This paper cites Consistency-aware anchor pyramid network for crowd localization.IEEE Trans.

Count Anything Consistency-aware anchor pyramid network for crowd localization.IEEE Trans

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 983734b4-49d3-4c9c-8f65-ac3c48b79b7c · outbound

This paper cites Kevin Zhou, and Jie Chen.

Count Anything Kevin Zhou, and Jie Chen

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 4daf316a-be6a-4710-af04-6ca96f2af244 · outbound

This paper cites TasselNet: Counting maize tassels in the wild via local counts regression network.Plant Methods, 13(1):79, 2017.

Count Anything TasselNet: Counting maize tassels in the wild via local counts regression network.Plant Methods, 13(1):79, 2017

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation d1572d6c-4809-4ae2-96af-cb3f42e83ce4 · outbound

This paper cites LVIS: A dataset for large vocabulary instance segmentation.

Count Anything LVIS: A dataset for large vocabulary instance segmentation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 91d7954f-f005-4635-82a0-a32aaac24223 · outbound

This paper cites Plummer, Liwei Wang, Chris M.

Count Anything Plummer, Liwei Wang, Chris M

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 3b8d06b8-2d47-40d5-b6b2-4b9689b3eb1d · outbound

This paper cites SAM 3: Segment anything with concepts.

Count Anything SAM 3: Segment anything with concepts

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 7187e3b9-ddc3-4f8c-966b-0d46a1ef3084 · outbound

This paper cites End-to-End Object Detection with Transformers.

Count Anything End-to-End Object Detection with Transformers

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 6f4d578c-6829-4756-9b9c-976f21f15b24 · outbound

This paper cites A Low-Shot Object Counting Network With Iterative Prototype Adaptation.

Count Anything A Low-Shot Object Counting Network With Iterative Prototype Adaptation

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 413186cf-90d8-46e5-89e7-f49abe0882c2 · outbound

This paper cites Open-World Text-Specified Object Counting.

Count Anything Open-World Text-Specified Object Counting

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 23e8355a-2bb2-43cc-941e-6e6c77853fe2 · outbound

This paper cites YOLO-Count: Differentiable object counting for text-to-image generation.

Count Anything YOLO-Count: Differentiable object counting for text-to-image generation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 4629d0ce-d1a1-42f5-972e-d41f5f423404 · outbound

This paper cites an unresolved cited work.

Count Anything Unresolved cited work

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation ed020fda-f622-4682-ad1c-d1739aad766b · outbound

This paper cites CountSE: Soft exemplar open-set object counting.

Count Anything CountSE: Soft exemplar open-set object counting

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation ba4e0e3b-aa11-4fbc-9f1c-6f74fc09ff3e · outbound

This paper cites Grounded Language-Image Pre-Training.

Count Anything Grounded Language-Image Pre-Training

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation fa420fc3-1512-4b8f-85d8-04f38d0046f6 · outbound

This paper cites YOLO-World: Real- time open-vocabulary object detection.

Count Anything YOLO-World: Real- time open-vocabulary object detection

Reference 43

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 4be3b68e-02e4-4935-8707-558e813dd816 · outbound

This paper cites Grounding DINO: Marrying DINO with grounded pre-training for open-set object detection.

Count Anything Grounding DINO: Marrying DINO with grounded pre-training for open-set object detection

Reference 44

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 508d78ff-6fb3-4708-a945-2c404eac34d2 · outbound

This paper cites YOLOE: Real-time seeing anything.

Count Anything YOLOE: Real-time seeing anything

Reference 45

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 15e41cbc-a6db-4a63-9415-bb8a1fef83d7 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Count Anything Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 46

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation d9af2e24-0bbc-47e5-8c19-9ea49d8e249b · outbound

This paper cites Decoupled weight decay regularization.

Count Anything Decoupled weight decay regularization

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 994c78b5-a877-45a3-82a0-9cda1a37373d · outbound

This paper cites Redesigning Multi-Scale Neural Network for Crowd Counting.IEEE Trans.

Count Anything Redesigning Multi-Scale Neural Network for Crowd Counting.IEEE Trans

Reference 48

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 31587b49-fed6-40a2-9f3f-29d62363d540 · outbound

This paper cites CSRNet: Dilated convolutional neural networks for understanding the highly congested scenes.

Count Anything CSRNet: Dilated convolutional neural networks for understanding the highly congested scenes

Reference 49

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 43d549f5-ee7b-4186-8227-00e798db2901 · outbound

This paper cites Scale Aggregation Network for Accurate and Efficient Crowd Counting.

Count Anything Scale Aggregation Network for Accurate and Efficient Crowd Counting

Reference 50

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 6ba006a7-16b5-4df6-8793-aa905500f58d · outbound

This paper cites Bayesian loss for crowd count estimation with point supervision.

Count Anything Bayesian loss for crowd count estimation with point supervision

Reference 51

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 9ba95bc5-fdef-4134-b59c-f851aa2d1700 · outbound

This paper cites CounTR: Transformer-based generalised visual counting.

Count Anything CounTR: Transformer-based generalised visual counting

Reference 52

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation fb98ea10-afdb-4b4b-b1a7-130b0c000aa3 · outbound

This paper cites Point, Segment and Count: A generalized framework for object counting.

Count Anything Point, Segment and Count: A generalized framework for object counting

Reference 53

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 27c0ef15-3c02-4e31-9ad1-17e384a7a9f0 · outbound

This paper cites DA VE: A detect-and-verify paradigm for low-shot counting.

Count Anything DA VE: A detect-and-verify paradigm for low-shot counting

Reference 54

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 3d8180e9-ed43-4047-89d5-182cabc4e506 · outbound

This paper cites Open-World Object Counting in Videos.

Count Anything Open-World Object Counting in Videos

Reference 55

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 5123dd28-3b19-4f34-8ade-b75c222f5da4 · outbound

This paper cites NWPU-Crowd: A large-scale benchmark for crowd counting and localization.IEEE Trans.

Count Anything NWPU-Crowd: A large-scale benchmark for crowd counting and localization.IEEE Trans

Reference 56

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation ba91e2ed-3eb4-4d55-a254-59cdf5d414de · outbound

This paper cites Badhon, Curtis Pozniak, Benoit de Solan, Andreas Hund, Scott C.

Count Anything Badhon, Curtis Pozniak, Benoit de Solan, Andreas Hund, Scott C

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 44741175-71e9-4a7d-8004-97cc17e02782 · outbound

This paper cites AGAR: A microbial colony dataset for deep learning detection, 2021.

Count Anything AGAR: A microbial colony dataset for deep learning detection, 2021

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 8669e0bc-53e9-461e-a9b1-433300dbb9ae · outbound

This paper cites OmniCount: Multi-label object counting with semantic-geometric priors.

Count Anything OmniCount: Multi-label object counting with semantic-geometric priors

Reference 59

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 300a3687-5d10-406d-b265-3667f8847a54 · outbound

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

Count Anything DOTA: A large-scale dataset for object detection in aerial images

Reference 60

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 23a9e17b-6e07-461b-8668-0c6a1b98ba71 · outbound

This paper cites xView: Objects in Context in Overhead Imagery.

Count Anything xView: Objects in Context in Overhead Imagery

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-06-28T23:02:46.008990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d6bdd6c4-ce76-4c58-8dd8-f54ea06c09b6 · outbound

This paper cites The Cityscapes Dataset for Semantic Urban Scene Understanding.

Count Anything The Cityscapes Dataset for Semantic Urban Scene Understanding

Reference 62

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 1147b502-7b45-441e-b7f8-209025241923 · outbound

This paper cites Jackson, Nabeel Khalid, Nicola Bevan, Timothy Dale, Andreas Dengel, Sheraz Ahmed, Johan Trygg, and Rickard Sjögren.

Count Anything Jackson, Nabeel Khalid, Nicola Bevan, Timothy Dale, Andreas Dengel, Sheraz Ahmed, Johan Trygg, and Rickard Sjögren

Reference 63

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 5232632a-9ca6-4de8-a8c3-4447aa11800e · outbound

This paper cites SoybeanNet: Transformer-based convolutional neural network for soybean pod counting from unmanned aerial vehicle (UA V) images.Comput.

Count Anything SoybeanNet: Transformer-based convolutional neural network for soybean pod counting from unmanned aerial vehicle (UA V) images.Comput

Reference 64

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 942c71d5-a1d9-453e-855e-62164b0f8771 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Count Anything Learning Transferable Visual Models From Natural Language Supervision

Reference 65

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 3ce50b1f-9224-4898-8dcb-9deee3bfeb7f · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick.

Count Anything Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick

Reference 66

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

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Observation 3f380b06-c22c-4986-87b2-bbda98ae15a9 · outbound

This paper cites MedMNIST v2: A large-scale lightweight benchmark for 2D and 3D biomedical image classification.

Count Anything MedMNIST v2: A large-scale lightweight benchmark for 2D and 3D biomedical image classification

Reference 67

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1636098d-d0d7-4390-84d8-086bf5388de0 · outbound

This paper cites Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M.

Count Anything Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M

Reference 68

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Observation 9dfbe512-ec2d-4c75-96b0-d0d1baee79fb · outbound

This paper cites MSeg: A composite dataset for multi-domain semantic segmentation.

Count Anything MSeg: A composite dataset for multi-domain semantic segmentation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Observation fb6970d8-a9a1-4283-9df3-74019330176e · outbound

This paper cites BigDetection: A large-scale benchmark for improved object detector pre-training.

Count Anything BigDetection: A large-scale benchmark for improved object detector pre-training

Reference 70

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0de2e9d9-9047-4057-ab94-37eff643b9ba · outbound

This paper cites rebar counting dataset.

Count Anything rebar counting dataset

Reference 71

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6621be59-1d3b-4f82-b2d2-3564d0621f97 · outbound

This paper cites an unresolved cited work.

Count Anything Unresolved cited work

Reference 72

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e12f41d-71e0-4df0-9036-4d5429d63b49 · outbound

This paper cites Object Detection in Optical Remote Sensing Images: A survey and a new benchmark.ISPRS J.

Count Anything Object Detection in Optical Remote Sensing Images: A survey and a new benchmark.ISPRS J

Reference 73

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01084f7b-c8c2-407a-8dd8-017f1d0f95a3 · outbound

This paper cites Object Detection in Aerial Images: A large-scale benchmark and challenges.IEEE Trans.

Count Anything Object Detection in Aerial Images: A large-scale benchmark and challenges.IEEE Trans

Reference 74

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5069f87a-521c-4430-bc05-74cd9d22b34f · outbound

This paper cites Learning RoI Transformer for Oriented Object Detection in Aerial Images.

Count Anything Learning RoI Transformer for Oriented Object Detection in Aerial Images

Reference 75

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e6d0095-a388-4eda-acd5-7274e0bc0ecb · outbound

This paper cites Detection, Tracking, and Counting Meets Drones in Crowds: A benchmark.

Count Anything Detection, Tracking, and Counting Meets Drones in Crowds: A benchmark

Reference 76

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01711227-aaac-4ad6-a3f1-df4d5678a4d1 · outbound

This paper cites NWPU-MOC: A benchmark for fine-grained multicategory object counting in aerial images.IEEE Trans.

Count Anything NWPU-MOC: A benchmark for fine-grained multicategory object counting in aerial images.IEEE Trans

Reference 77

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Observation 189bac5c-8965-4eec-98c8-7d52c2ec8789 · outbound

This paper cites Multi-Class Geospatial Object Detection and Geographic Image Classification Based on Collection of Part Detectors.ISPRS J.

Count Anything Multi-Class Geospatial Object Detection and Geographic Image Classification Based on Collection of Part Detectors.ISPRS J

Reference 78

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd9436ac-ffbb-486f-add8-0570034495dd · outbound

This paper cites A Survey on Object Detection in Optical Remote Sensing Images.ISPRS J.

Count Anything A Survey on Object Detection in Optical Remote Sensing Images.ISPRS J

Reference 79

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a51d06c-059e-4a0a-956b-023072611f4c · outbound

This paper cites Learning Rotation-Invariant Convolutional Neural Networks for Object Detection in VHR Optical Remote Sensing Images.IEEE Trans.

Count Anything Learning Rotation-Invariant Convolutional Neural Networks for Object Detection in VHR Optical Remote Sensing Images.IEEE Trans

Reference 80

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65e7db35-1ff0-4a37-a63d-03ba16d8f933 · outbound

This paper cites Accurate Object Localization in Remote Sensing Images Based on Convolutional Neural Networks.IEEE Trans.

Count Anything Accurate Object Localization in Remote Sensing Images Based on Convolutional Neural Networks.IEEE Trans

Reference 81

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Observation 5be07e47-3077-4411-980b-46ed22b71a16 · outbound

This paper cites Elliptic Fourier Transformation-Based Histograms of Oriented Gradients for Rotationally Invariant Object Detection in Remote-Sensing Images.Int.

Count Anything Elliptic Fourier Transformation-Based Histograms of Oriented Gradients for Rotationally Invariant Object Detection in Remote-Sensing Images.Int

Reference 82

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Observation a93b901a-c493-43a8-b504-50a7ca2b85df · outbound

This paper cites Enhancing people localisation in drone imagery for better crowd management by utilising every pixel in high-resolution images.

Count Anything Enhancing people localisation in drone imagery for better crowd management by utilising every pixel in high-resolution images

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:02:46.005364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0383390d-2021-4c3c-9895-3a206b2dd435 · outbound

This paper cites CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.Med.

Count Anything CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting.Med

Reference 84

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 289dae04-9c41-4edd-9be4-35dcce3d1bc2 · outbound

This paper cites EndoNuke: Nuclei detection dataset for estrogen and progesterone stained IHC endometrium scans.Data, 7(6):75, 2022.

Count Anything EndoNuke: Nuclei detection dataset for estrogen and progesterone stained IHC endometrium scans.Data, 7(6):75, 2022

Reference 85

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b2c7590-ba56-4308-8bf2-e8129c19f25c · outbound

This paper cites Lizard: A large-scale dataset for colonic nuclear instance segmentation and classification.

Count Anything Lizard: A large-scale dataset for colonic nuclear instance segmentation and classification

Reference 86

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3a05912-5813-45f6-84f0-2c51225f8ff6 · outbound

This paper cites A Multi-Organ Nucleus Segmentation Challenge.IEEE Trans.

Count Anything A Multi-Organ Nucleus Segmentation Challenge.IEEE Trans

Reference 87

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Observation bfbcf1e4-7cd1-4cc5-9f35-c7d48862ae8c · outbound

This paper cites Atteya, Hagar Hussein, Kareem Hosny Mohammed, Ehab Hafiz, Maha A.

Count Anything Atteya, Hagar Hussein, Kareem Hosny Mohammed, Ehab Hafiz, Maha A

Reference 88

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Observation d02d7a0e-f518-4898-ab3f-36f0296d8b40 · outbound

This paper cites BriFiSeg: a deep learning-based method for semantic and instance segmentation of nuclei in brightfield images.

Count Anything BriFiSeg: a deep learning-based method for semantic and instance segmentation of nuclei in brightfield images

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:02:45.999375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0f876542-169f-44b6-81f6-78cddfe5660e · outbound

This paper cites Learning To Count Objects in Images.

Count Anything Learning To Count Objects in Images

Reference 90

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0919e59-4a8f-497d-b07d-b6a62c9b4c7f · outbound

This paper cites Laine, Pedro M.

Count Anything Laine, Pedro M

Reference 91

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c5d6774-6ccd-4209-8046-d7ac6fc3ace4 · outbound

This paper cites an unresolved cited work.

Count Anything Unresolved cited work

Reference 92

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05bbedf0-488e-41b7-a654-fa396fc8df9d · outbound

This paper cites people’s heads.

Count Anything people’s heads

Reference 93

Resolution: malformed identifier; arxiv_id, observed 2026-06-28T23:02:46.003533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 89b7ce42-a51b-40c0-a634-9b2eb5464713 · outbound

This paper cites Some source datasets adopt standard COCO-style JSON annotations, such as Objects365-2020, FSCD-LVIS, and LIVECell.

Count Anything Some source datasets adopt standard COCO-style JSON annotations, such as Objects365-2020, FSCD-LVIS, and LIVECell

Reference 94

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03538ef8-8d7f-4d8f-bd95-e1fe6fb075ea · outbound

This paper cites VOC-style datasets use XML files to record the target category, bounding box, difficult flag, and related fields for each image.

Count Anything VOC-style datasets use XML files to record the target category, bounding box, difficult flag, and related fields for each image

Reference 95

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8f73e8b-9396-4e86-9191-ea011c1ba80c · outbound

This paper cites 35439": {.

Count Anything 35439": {

Reference 96

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9af3dd56-38c4-4565-beba-34ef26e517ec · outbound

This paper cites Public datasets often adopt different naming conventions, such as differences in capitalization, singular/plural forms, spaces, underscores, and special characters.

Count Anything Public datasets often adopt different naming conventions, such as differences in capitalization, singular/plural forms, spaces, underscores, and special characters

Reference 97

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f890884-7841-4bed-a439-0e9e291b3cf3 · outbound

This paper cites one instance, one count.

Count Anything one instance, one count

Reference 98

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fd56a71-b145-42b5-a32d-fe23ecfd3fa2 · outbound

This paper cites For category consolidation in a multi-source dataset, it is not appropriate to simply promote all subclasses to their parent class.

Count Anything For category consolidation in a multi-source dataset, it is not appropriate to simply promote all subclasses to their parent class

Reference 99

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2058c412-b5d3-4b52-9566-05c255a45aa4 · outbound

This paper cites Since the dataset covers multiple visual domains, image resolutions vary substantially across data sources.

Count Anything Since the dataset covers multiple visual domains, image resolutions vary substantially across data sources

Reference 100

Resolution: unresolved; no resolver link, observed 2026-06-28T23:02:05.250519Z

Source-reported events for the cited work

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Outbound references

Pith citing papers