Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting | Paper Citation Record

Observation ff9d4117-b719-41dd-bb7a-c7e9829871fe · outbound

This paper cites Slic superpixels.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Slic superpixels

Reference 1

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Observation 1bd2919a-252f-4841-9665-b017b2e0ed9a · outbound

This paper cites Counting in the wild.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Counting in the wild

Reference 2

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Observation 3c54308b-d902-4c0c-91db-585f7ebba698 · outbound

This paper cites Divide and grow: Capturing huge diversity in crowd images with incrementally growing cnn.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Divide and grow: Capturing huge diversity in crowd images with incrementally growing cnn

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.068927Z

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Observation 5f3b0464-2f4f-4fb4-bb83-33500da0d78a · outbound

This paper cites The watershed transformation ap- plied to image segmentation.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting The watershed transformation ap- plied to image segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.053636Z

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Observation c6f20c18-dc3e-4d62-ad86-8eb4f95bce9c · outbound

This paper cites Crowdnet: A deep convolutional network for dense crowd counting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowdnet: A deep convolutional network for dense crowd counting

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.039038Z

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Observation 732caf99-7af7-4563-953d-9b22cd8ebbef · outbound

This paper cites A uniﬁed multi-scale deep convolutional neural network for fast object detection.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting A uniﬁed multi-scale deep convolutional neural network for fast object detection

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.024585Z

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Observation 7da1fbc1-456d-4290-af96-b1f2554b01bd · outbound

This paper cites Scale aggregation network for accurate and efﬁcient crowd count- ing.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Scale aggregation network for accurate and efﬁcient crowd count- ing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:01.009381Z

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Observation f25bfa63-b4ba-4ccc-b56d-638c95c13a3d · outbound

This paper cites Privacy preserving crowd monitoring: Counting people without people models or tracking.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Privacy preserving crowd monitoring: Counting people without people models or tracking

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.995124Z

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Observation 98dabb2d-f198-4222-b886-4481d7c58e49 · outbound

This paper cites Feature mining for localised crowd counting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Feature mining for localised crowd counting

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.980822Z

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Observation 59dba188-3fb2-4059-bade-ada4a4e1750d · outbound

This paper cites Re- verse attention for salient object detection.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Re- verse attention for salient object detection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.966274Z

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Observation e61f944b-e53d-4d80-ba8b-8a040453df35 · outbound

This paper cites Convolutional neural networks for counting ﬁsh in ﬁsheries surveillance video.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Convolutional neural networks for counting ﬁsh in ﬁsheries surveillance video

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.952063Z

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Observation 5f15c5c1-b1e9-4715-83b7-b96102db3d4d · outbound

This paper cites Laplacian pyramid reconstruction and reﬁnement for semantic segmentation.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Laplacian pyramid reconstruction and reﬁnement for semantic segmentation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.937756Z

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Observation d58c08dc-745e-41d8-805d-fdb995ca0f85 · outbound

This paper cites Hypercolumns for object segmentation and ﬁne-grained localization.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Hypercolumns for object segmentation and ﬁne-grained localization

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.923284Z

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Observation a6a73116-b43a-4661-a07e-82a3e218b5be · outbound

This paper cites Deeply supervised salient object detection with short connections.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Deeply supervised salient object detection with short connections

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.909097Z

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Observation 2bf6716c-19bd-421c-b5e5-41c2185f7579 · outbound

This paper cites an unresolved cited work.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Unresolved cited work

Reference 15

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Observation ce73b2b8-996c-434b-87c8-3854ce261879 · outbound

This paper cites Finding tiny faces.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Finding tiny faces

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.879988Z

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Observation deaff888-8159-4e52-8f96-0ad8e1caa283 · outbound

This paper cites Multi-source multi-scale counting in extremely dense crowd images.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Multi-source multi-scale counting in extremely dense crowd images

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.864904Z

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Observation 66bee9a5-3657-4676-a0ad-f18a262b9780 · outbound

This paper cites De- tecting humans in dense crowds using locally-consistent scale prior and global occlusion reasoning.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting De- tecting humans in dense crowds using locally-consistent scale prior and global occlusion reasoning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.850826Z

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Observation 315e235c-0046-4e75-ab24-3a81a7c40606 · outbound

This paper cites Composition loss for counting, density map estimation and localization in dense crowds.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Composition loss for counting, density map estimation and localization in dense crowds

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.836359Z

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Observation 7352ca3e-8843-4e4f-9341-570479cbc0e6 · outbound

This paper cites Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:33:00.030995Z

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Observation 995e7282-7eb9-4092-a85a-51900a0fba49 · outbound

This paper cites Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T10:32:59.626326Z

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Observation cb4eea37-6eff-4c78-95c6-ef392896c413 · outbound

This paper cites Learning to count objects in images.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Learning to count objects in images

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.821812Z

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Observation 3377996a-66e2-481f-b17a-f937e7677f4e · outbound

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

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Scale-aware fast r-cnn for pedestrian detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.807851Z

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Observation 930aa718-c17c-430e-984f-0086e290d465 · outbound

This paper cites Estimating the number of people in crowded scenes by mid based foreground segmentation and head-shoulder detection.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Estimating the number of people in crowded scenes by mid based foreground segmentation and head-shoulder detection

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.793804Z

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Observation e29a6ce7-7e26-47d3-8066-bc911a9f67b0 · outbound

This paper cites Markov random ﬁeld models in computer vision.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Markov random ﬁeld models in computer vision

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.779106Z

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Observation 977fad28-d8a1-424d-8176-6aaabd1f2eee · outbound

This paper cites Crowded scene analysis: A sur- vey.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowded scene analysis: A sur- vey

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.764693Z

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Observation ab8d8450-d720-439c-8940-33c6c8d7c980 · outbound

This paper cites Anomaly detection and localization in crowded scenes.IEEE transactions on pattern analysis and machine intelligence , 36(1):18–32, 2014.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Anomaly detection and localization in crowded scenes.IEEE transactions on pattern analysis and machine intelligence , 36(1):18–32, 2014

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.749833Z

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Observation 269a40d1-dc06-4f5f-84e7-a5c416b94616 · outbound

This paper cites Csrnet: Di- lated convolutional neural networks for understanding the highly congested scenes.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Csrnet: Di- lated convolutional neural networks for understanding the highly congested scenes

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.734829Z

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Observation b6d2557d-758b-44e2-b095-2fbe1c4eb4db · outbound

This paper cites Reﬁnenet: Multi-path reﬁnement networks for high- resolution semantic segmentation.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Reﬁnenet: Multi-path reﬁnement networks for high- resolution semantic segmentation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.720802Z

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Observation 8b201e56-e1f3-4418-adea-5a685f093c29 · outbound

This paper cites Feature pyramid networks for object detection.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Feature pyramid networks for object detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.706688Z

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Observation 6aa7c2d3-1d14-4004-b77e-a0658f084efb · outbound

This paper cites ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd Understanding.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd Understanding

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:32:59.991994Z

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Observation fd8967d7-6057-4dc1-9777-445b81afb7c1 · outbound

This paper cites Path aggregation network for instance segmentation.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Path aggregation network for instance segmentation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.691535Z

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Observation f89d58dd-8b97-4d55-88af-3646012be3c4 · outbound

This paper cites Context- aware crowd counting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Context- aware crowd counting

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.677552Z

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Observation 07e646fd-9ccf-4cf2-b309-2364b5f272de · outbound

This paper cites Bagdanov.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Bagdanov

Reference 34

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Observation 7388dd85-cc35-45cc-93e3-e2dfc9b8349b · outbound

This paper cites Tasselnet: Counting maize tassels in the wild via local counts regression network.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Tasselnet: Counting maize tassels in the wild via local counts regression network

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.648260Z

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Observation 32f27f57-9bcb-47ba-be24-fdd6787c90f1 · outbound

This paper cites Anomaly detection in crowded scenes.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Anomaly detection in crowded scenes

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.633377Z

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Observation 2e9c758f-427d-4690-bfb6-5dd326ce7bf1 · outbound

This paper cites Ssh: Single stage headless face detector.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Ssh: Single stage headless face detector

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.619446Z

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Observation 8ed235cd-ea97-4b20-89ec-a65b79235ac8 · outbound

This paper cites Towards perspective-free object counting with deep learning.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Towards perspective-free object counting with deep learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.605350Z

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Observation bc826fe0-273e-4049-8d17-8255e8172dec · outbound

This paper cites Count forest: Co-voting uncertain number of targets using random forest for crowd density estimation.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Count forest: Co-voting uncertain number of targets using random forest for crowd density estimation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.591158Z

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Observation fbf3b307-4fc9-4cf2-b6d8-f602e5699fd7 · outbound

This paper cites Learning to reﬁne object segments.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Learning to reﬁne object segments

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.577008Z

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Observation eddf6d1c-a8ec-4be4-b6c2-cac546f92209 · outbound

This paper cites Top-down visual saliency guided by captions.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Top-down visual saliency guided by captions

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.562409Z

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Observation 521ea595-7ce7-40d9-bd6d-d9c12fc0792c · outbound

This paper cites Hy- perface: A deep multi-task learning framework for face de- tection, landmark localization, pose estimation, and gender recognition.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Hy- perface: A deep multi-task learning framework for face de- tection, landmark localization, pose estimation, and gender recognition

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.547496Z

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Observation 4f416799-4de8-414a-aff0-3eefccbe6636 · outbound

This paper cites Iterative crowd counting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Iterative crowd counting

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.532462Z

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Observation bba5d74c-8203-4537-be4d-d6638a91c548 · outbound

This paper cites Density-aware person detection and tracking in crowds.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Density-aware person detection and tracking in crowds

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.517584Z

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Observation 983b4a08-8cf2-40af-ab8b-c7ee27c61fa0 · outbound

This paper cites A multi-scale cnn for affordance segmentation in rgb images.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting A multi-scale cnn for affordance segmentation in rgb images

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.502733Z

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Observation 31180f59-fd79-4a83-8766-b55634cc4e5f · outbound

This paper cites Crowd counting using multiple local features.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowd counting using multiple local features

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.487259Z

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Observation ed5c67ac-f946-4bc4-abb4-a96afbb630ed · outbound

This paper cites Top-down feed- back for crowd counting convolutional neural network.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Top-down feed- back for crowd counting convolutional neural network

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.455336Z

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Observation 43114644-92e8-4c44-a551-20ef08663779 · outbound

This paper cites Venkatesh Babu.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Venkatesh Babu

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.440429Z

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Observation 4df663f2-0159-4764-8c18-a3e90c82a1dc · outbound

This paper cites Crowd counting via adversarial cross-scale consistency pursuit.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowd counting via adversarial cross-scale consistency pursuit

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.425401Z

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Observation bc8743b2-a593-4af0-a356-2041fdb3c239 · outbound

This paper cites Re- visiting perspective information for efﬁcient crowd counting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Re- visiting perspective information for efﬁcient crowd counting

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.410341Z

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Observation 9fc216f1-1b08-4b19-b7dd-976753529fe5 · outbound

This paper cites Crowd counting with deep negative correlation learning.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowd counting with deep negative correlation learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.395104Z

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Observation 7f4601d4-e803-4781-9205-fe7c49ad17de · outbound

This paper cites Beyond Skip Connections: Top-Down Modulation for Object Detection.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Beyond Skip Connections: Top-Down Modulation for Object Detection

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-14T10:32:59.774770Z

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Observation ac2a3a57-41a2-450b-96c4-b802d97efe53 · outbound

This paper cites Simonyan and A.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Simonyan and A

Reference 53

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This paper cites Inverse attention guided deep crowd counting network.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Inverse attention guided deep crowd counting network

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.370411Z

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Observation 04beae6d-c795-467a-9685-395178c56107 · outbound

This paper cites Sindagi and Vishal M.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Sindagi and Vishal M

Reference 55

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Observation 4528570d-4223-4b81-9a17-bc8427a4d97b · outbound

This paper cites Sindagi and Vishal M.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Sindagi and Vishal M

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.340244Z

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

Observation 38228ac4-d587-46ef-9609-cb8d0de5734a · outbound

This paper cites A survey of re- cent advances in cnn-based single image crowd counting and density estimation.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting A survey of re- cent advances in cnn-based single image crowd counting and density estimation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.325890Z

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Observation 0ba3e601-4f56-40f9-985b-c05c8745e280 · outbound

This paper cites HA-CCN: Hierarchical Attention-based Crowd Counting Network.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting HA-CCN: Hierarchical Attention-based Crowd Counting Network

Reference 58

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Observation 028e3851-e079-469f-ac6b-a63db219ece2 · outbound

This paper cites Trafﬁc ﬂow from a low frame rate city camera.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Trafﬁc ﬂow from a low frame rate city camera

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.310967Z

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Observation 75d90742-6757-47ca-b3e5-8569e5b119ce · outbound

This paper cites Learning to count with cnn boosting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Learning to count with cnn boosting

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.296761Z

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Observation 33a994e1-39e2-4ec4-9913-1ec998ee2428 · outbound

This paper cites Residual regression with semantic prior for crowd counting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Residual regression with semantic prior for crowd counting

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.281999Z

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Observation 1a6ba59e-39de-4e5e-aa41-ea0663c27916 · outbound

This paper cites Deep people counting in extremely dense crowds.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Deep people counting in extremely dense crowds

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.267341Z

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Observation 283d7c45-be60-4b38-ab08-4410cd0ca571 · outbound

This paper cites Learning from Synthetic Data for Crowd Counting in the Wild.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Learning from Synthetic Data for Crowd Counting in the Wild

Reference 63

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Observation 0fdc38ad-477a-4aab-8e96-3a3294e3f76c · outbound

This paper cites Spatiotem- poral modeling for crowd counting in videos.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Spatiotem- poral modeling for crowd counting in videos

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.252980Z

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.

Observation 6e0b70c7-7bfe-4e67-bdee-8b304d7e7859 · outbound

This paper cites Crowd density estimation based on rich features and random projection forest.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowd density estimation based on rich features and random projection forest

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.238413Z

Source-reported events for the cited work

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Observation 4459246b-8194-48fd-bb93-a334764d4d56 · outbound

This paper cites Multi-scale bidirectional fcn for object skeleton extraction.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Multi-scale bidirectional fcn for object skeleton extraction

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.223726Z

Source-reported events for the cited work

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Observation f0c600d0-c447-4747-b13b-ee4117d79587 · outbound

This paper cites an unresolved cited work.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-14T10:33:00.208830Z

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.

Observation 94798c85-ea59-4a9d-a835-f116a32b5328 · outbound

This paper cites Crowd analysis: a survey.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowd analysis: a survey

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.193569Z

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.

Observation 8cfc7981-0556-4b91-8a20-3c5410a17b92 · outbound

This paper cites Cross-scene crowd counting via deep convolutional neural networks.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Cross-scene crowd counting via deep convolutional neural networks

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.179219Z

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Observation ff5d8a33-bcaa-421f-b12a-50e8920e83fd · outbound

This paper cites Wide-area crowd counting via ground-plane density maps and multi-view fusion cnns.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Wide-area crowd counting via ground-plane density maps and multi-view fusion cnns

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.164410Z

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Observation bcfaae99-3cb3-4238-96a5-28ad54315a4a · outbound

This paper cites Understanding trafﬁc density from large- scale web camera data.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Understanding trafﬁc density from large- scale web camera data

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.149934Z

Source-reported events for the cited work

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Observation 18fe6195-8785-458b-9076-e3a36c4082d0 · outbound

This paper cites Costeira, and Jos M.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Costeira, and Jos M

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.134129Z

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.

Observation 69c308d9-22a4-4ea7-9f75-2dcb352f3efa · outbound

This paper cites Progressive attention guided recurrent net- work for salient object detection.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Progressive attention guided recurrent net- work for salient object detection

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.117818Z

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.

Observation 7145f4b3-dbe6-41d6-a889-81b6b54fbdd3 · outbound

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

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Single-image crowd counting via multi-column convolutional neural network

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.103477Z

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.

Observation 4ec2b998-6662-4b4d-95aa-b440ef94706a · outbound

This paper cites Leveraging heterogeneous auxiliary tasks to assist crowd counting.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Leveraging heterogeneous auxiliary tasks to assist crowd counting

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.088785Z

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.

Observation 80a77bb5-af1f-43cc-9968-37af64bdd80c · outbound

This paper cites Defocus blur detection via multi-stream bottom-top-bottom fully convolutional network.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Defocus blur detection via multi-stream bottom-top-bottom fully convolutional network

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.073554Z

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.

Observation 8e7a7b03-40a1-4af4-b3eb-88125d7c0b67 · outbound

This paper cites Crowd tracking with dynamic evolution of group structures.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Crowd tracking with dynamic evolution of group structures

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.057633Z

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.

Observation a684c43b-4f9d-4bc0-bb22-ebc79ca3355b · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-14T10:32:59.895490Z

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Observation ab76da81-5064-4801-9d29-784e0c8619d2 · outbound

This paper cites IEEE, 2009.

Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting IEEE, 2009

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:33:00.471703Z

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