Paper Citation Record · LEDGER

Crowd Counting with Deep Structured Scale Integration Network

As of 22 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:1908.08692.

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

pith.paper-citation-record.v1
1908.08692 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:37:37.887940Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

49 of 49 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1522b391-1808-45b4-ba5e-aa77ccebc05d · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Divide and grow: Capturing huge diversity in crowd images with incrementally growing cnn

Reference 1

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Observation b6970c66-5fbe-4a39-8f35-669b3709770a · outbound

This paper cites SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation.

Crowd Counting with Deep Structured Scale Integration Network SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Reference 2

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Observation 25b3810d-08cc-49e6-bde5-06fa88049874 · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Crowdnet: A deep convolutional network for dense crowd counting

Reference 3

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Observation d63b571c-9aa8-402a-9035-9e44ca5c519f · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Scale aggregation network for accurate and efﬁcient crowd count- ing

Reference 4

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Observation da1cf41c-f8fe-429b-ae2b-d31d510e513a · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs.

Crowd Counting with Deep Structured Scale Integration Network Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolu- tion, and fully connected crfs

Reference 5

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Observation ee1aa863-e8ef-43c4-9f95-e014d8080b46 · outbound

This paper cites Crf-cnn: Modeling structured information in human pose estimation.

Crowd Counting with Deep Structured Scale Integration Network Crf-cnn: Modeling structured information in human pose estimation

Reference 6

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Observation bf2f971e-0ca5-4e00-87de-683b3e444e34 · outbound

This paper cites Pcc net: Perspective crowd counting via spatial convolutional network.

Crowd Counting with Deep Structured Scale Integration Network Pcc net: Perspective crowd counting via spatial convolutional network

Reference 7

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Observation eee2e52e-8fcb-472f-97c1-f491a4add09e · outbound

This paper cites Marked point processes for crowd counting.

Crowd Counting with Deep Structured Scale Integration Network Marked point processes for crowd counting

Reference 8

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Observation 8249d808-cddd-4e86-af4e-27774e1d599c · outbound

This paper cites Deep residual learning for image recognition.

Crowd Counting with Deep Structured Scale Integration Network Deep residual learning for image recognition

Reference 9

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Observation 552d1138-19f0-4853-95a2-7a323f4bfeb9 · outbound

This paper cites Densely connected convolutional net- works.

Crowd Counting with Deep Structured Scale Integration Network Densely connected convolutional net- works

Reference 10

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Observation bf8a8c99-398d-46e2-a0b3-0f8d4f09b619 · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Multi-source multi-scale counting in extremely dense crowd images

Reference 11

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Observation a1433068-d6e9-41cc-9949-3f6ef2233411 · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Composition loss for counting, density map estima- tion and localization in dense crowds

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.455183Z

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Observation 3e03b9fc-dddf-4eda-9863-d06a3c982cfa · outbound

This paper cites Crowd counting by adaptively fusing predictions from an image pyramid.

Crowd Counting with Deep Structured Scale Integration Network Crowd counting by adaptively fusing predictions from an image pyramid

Reference 13

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Observation e2badad3-e428-4ed5-9736-e31aa5f0cfdb · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Crowd Counting with Deep Structured Scale Integration Network Adam: A Method for Stochastic Optimization

Reference 14

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Observation e85a1b58-9e91-47e6-8289-0c27f028fbcc · outbound

This paper cites Efﬁcient inference in fully connected crfs with gaussian edge potentials.

Crowd Counting with Deep Structured Scale Integration Network Efﬁcient inference in fully connected crfs with gaussian edge potentials

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.428328Z

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Observation e2a32c6c-36aa-4ae4-a3fa-5aab1d99a33f · outbound

This paper cites Conditional random ﬁelds: Probabilistic models for seg- menting and labeling sequence data.

Crowd Counting with Deep Structured Scale Integration Network Conditional random ﬁelds: Probabilistic models for seg- menting and labeling sequence data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.413867Z

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Observation 6abc1db8-ca21-4b2c-bbe6-1d078159b121 · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Csrnet: Di- lated convolutional neural networks for understanding the highly congested scenes

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.399106Z

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Observation 22a0a005-f830-4e94-aff0-0e1ff002f2ab · outbound

This paper cites Feature pyramid networks for object detection.

Crowd Counting with Deep Structured Scale Integration Network Feature pyramid networks for object detection

Reference 18

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Observation 5db8d46a-ba17-4742-ad54-d3ed9c42a5d1 · outbound

This paper cites Decidenet: Counting varying density crowds through attention guided detection and density estimation.

Crowd Counting with Deep Structured Scale Integration Network Decidenet: Counting varying density crowds through attention guided detection and density estimation

Reference 19

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Observation 7ec483c5-cd52-47d9-b7cc-d80282925e3c · outbound

This paper cites Crowd counting using deep recurrent spatial- aware network.

Crowd Counting with Deep Structured Scale Integration Network Crowd counting using deep recurrent spatial- aware network

Reference 20

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Observation 64ab284f-5443-4af1-92b4-4197d075812f · outbound

This paper cites Attentive crowd ﬂow machines.

Crowd Counting with Deep Structured Scale Integration Network Attentive crowd ﬂow machines

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.345994Z

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Observation 1f87f9ba-c6f4-42c7-bc6d-d57c2dbf1774 · outbound

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

Crowd Counting with Deep Structured Scale Integration Network ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd Understanding

Reference 22

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Observation 08a828c0-57b0-4e8c-bd1e-7d5765ac0784 · outbound

This paper cites Geometric and physical constraints for drone- based head plane crowd density estimation.

Crowd Counting with Deep Structured Scale Integration Network Geometric and physical constraints for drone- based head plane crowd density estimation

Reference 23

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Observation d705c06d-567f-49da-9100-4cda0a936e0f · outbound

This paper cites Context-Aware Crowd Counting.

Crowd Counting with Deep Structured Scale Integration Network Context-Aware Crowd Counting

Reference 24

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Observation e767a495-2000-4b64-ba9b-c27b31f96f5e · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Towards perspective-free object counting with deep learning

Reference 25

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Observation fa09265c-a049-4152-9f21-e4905b6272f1 · outbound

This paper cites Automatic differentiation in pytorch.

Crowd Counting with Deep Structured Scale Integration Network Automatic differentiation in pytorch

Reference 26

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Observation de6dfb38-1146-46d2-815f-525ff9f57c22 · outbound

This paper cites Crowd counting via multi-view scale aggre- gation networks.

Crowd Counting with Deep Structured Scale Integration Network Crowd counting via multi-view scale aggre- gation networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.295551Z

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Observation 1d866885-fc54-4a40-b93a-542d6defd284 · outbound

This paper cites Iterative crowd counting.

Crowd Counting with Deep Structured Scale Integration Network Iterative crowd counting

Reference 28

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Observation 5016e021-47ab-4b7c-ab58-367096f8092d · outbound

This paper cites Continuous conditional random ﬁelds for efﬁcient regression in large fully connected graphs.

Crowd Counting with Deep Structured Scale Integration Network Continuous conditional random ﬁelds for efﬁcient regression in large fully connected graphs

Reference 29

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Observation 2b6c5d3b-f8be-4905-bde5-62e833a432ac · outbound

This paper cites Switching convolutional neural network for crowd counting.

Crowd Counting with Deep Structured Scale Integration Network Switching convolutional neural network for crowd counting

Reference 30

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Observation 32c105d9-c43a-4bf4-85f4-4d0dfc34f35d · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Crowd counting via adversarial cross-scale consistency pursuit

Reference 31

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Observation 7481a7b3-7454-4500-a71e-c9f4ba73c4b1 · outbound

This paper cites Crowd count- ing with deep negative correlation learning.

Crowd Counting with Deep Structured Scale Integration Network Crowd count- ing with deep negative correlation learning

Reference 32

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Observation a6ba5eaa-0f44-48a5-bc28-c1d39f45d280 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Crowd Counting with Deep Structured Scale Integration Network Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 33

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Observation ead61083-651d-4070-a831-4b603dde2424 · outbound

This paper cites Cnn-based cas- caded multi-task learning of high-level prior and density esti- mation for crowd counting.

Crowd Counting with Deep Structured Scale Integration Network Cnn-based cas- caded multi-task learning of high-level prior and density esti- mation for crowd counting

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.212456Z

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Observation 445b2dac-a047-474f-b927-8ce0cb5f991a · outbound

This paper cites Generating high- quality crowd density maps using contextual pyramid cnns.

Crowd Counting with Deep Structured Scale Integration Network Generating high- quality crowd density maps using contextual pyramid cnns

Reference 35

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Observation 213d57eb-0ad6-4434-af17-cacdd8810802 · outbound

This paper cites Learning to count with cnn boosting.

Crowd Counting with Deep Structured Scale Integration Network Learning to count with cnn boosting

Reference 36

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Observation d2036bae-5973-4171-84dc-ef79cfaa3f25 · outbound

This paper cites Di- viding and aggregating network for multi-view action recog- nition.

Crowd Counting with Deep Structured Scale Integration Network Di- viding and aggregating network for multi-view action recog- nition

Reference 37

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Observation ed6a4b9b-d3e8-4dba-ae93-dda7fe226dfe · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

Crowd Counting with Deep Structured Scale Integration Network Image quality assessment: from error visibility to structural similarity

Reference 38

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Crowd Counting with Deep Structured Scale Integration Network Multi- scale structural similarity for image quality assessment

Reference 39

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This paper cites Spatiotempo- ral modeling for crowd counting in videos.

Crowd Counting with Deep Structured Scale Integration Network Spatiotempo- ral modeling for crowd counting in videos

Reference 40

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Observation 5872490f-2da1-40f4-ba64-65e751e13586 · outbound

This paper cites Learning deep struc- tured multi-scale features using attention-gated crfs for con- tour prediction.

Crowd Counting with Deep Structured Scale Integration Network Learning deep struc- tured multi-scale features using attention-gated crfs for con- tour prediction

Reference 41

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Observation 5203d93f-73c5-43df-b1c2-d8c888c24d3b · outbound

This paper cites Multi-scale convolutional neural networks for crowd counting.

Crowd Counting with Deep Structured Scale Integration Network Multi-scale convolutional neural networks for crowd counting

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.101600Z

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

Crowd Counting with Deep Structured Scale Integration Network Cross-scene crowd counting via deep convolutional neural networks

Reference 43

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This paper cites A bi-directional message passing model for salient object de- tection.

Crowd Counting with Deep Structured Scale Integration Network A bi-directional message passing model for salient object de- tection

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.072382Z

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Observation d40a7c67-d79c-4fd1-9d57-43065a03ded0 · outbound

This paper cites Crowd counting via scale-adaptive convolutional neural network.

Crowd Counting with Deep Structured Scale Integration Network Crowd counting via scale-adaptive convolutional neural network

Reference 45

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Observation c2f94e1d-dd97-4ee0-bf82-6b05129a83d3 · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Understanding trafﬁc density from large- scale web camera data

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.041647Z

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Observation 12804c2e-2602-44d5-86e0-bb2167ddc239 · outbound

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

Crowd Counting with Deep Structured Scale Integration Network Single-image crowd counting via multi-column convolutional neural network

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.026852Z

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Observation ee427ec6-6a98-4b80-b81c-758eb6c0a131 · outbound

This paper cites Loss functions for image restoration with neural networks.

Crowd Counting with Deep Structured Scale Integration Network Loss functions for image restoration with neural networks

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:38.011535Z

Source-reported events for the cited work

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Observation b382590e-ca62-48d8-ac5f-1d55794679b9 · outbound

This paper cites Conditional random ﬁelds as re- current neural networks.

Crowd Counting with Deep Structured Scale Integration Network Conditional random ﬁelds as re- current neural networks

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:37:37.996281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.