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Paper Citation Record · LEDGER

Bayesian Loss for Crowd Count Estimation with Point Supervision

As of 16 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:1908.03684.

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

pith.paper-citation-record.v1
1908.03684 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:14:57.854352Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

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  • verified fuzzy51
  • unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9bcd1a7e-8c0a-4b50-b5fa-6101eaef65ac · outbound

This paper cites Lempitsky, and Andrew Zisserman.

Bayesian Loss for Crowd Count Estimation with Point Supervision Lempitsky, and Andrew Zisserman

Reference 1

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Observation ad43f70d-00ef-40cf-85c9-1c92151568e7 · outbound

This paper cites Sajjan, R.

Bayesian Loss for Crowd Count Estimation with Point Supervision Sajjan, R

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 49ba45e2-2b5c-4043-bd5e-c42156d65a8d · outbound

This paper cites Venkatesh Babu.

Bayesian Loss for Crowd Count Estimation with Point Supervision Venkatesh Babu

Reference 3

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Source-reported events for the cited work

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Observation 4ed0255f-8c1c-4c05-808a-aa5c8d75bffc · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Scale aggregation network for accurate and efficient crowd count- ing

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 889455be-5551-4cd0-9a9b-adfd6e1b67d3 · outbound

This paper cites Chan, Zhang-Sheng John Liang, and Nuno Vas- concelos.

Bayesian Loss for Crowd Count Estimation with Point Supervision Chan, Zhang-Sheng John Liang, and Nuno Vas- concelos

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation bbb0aae3-b2b6-499b-a91d-bcc4175711f1 · outbound

This paper cites Selvaraju, Dhruv Batra, and Devi Parikh.

Bayesian Loss for Crowd Count Estimation with Point Supervision Selvaraju, Dhruv Batra, and Devi Parikh

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation cf709351-9afb-4cb3-9afe-06320a2fa3a8 · outbound

This paper cites Cumulative attribute space for age and crowd density estimation.

Bayesian Loss for Crowd Count Estimation with Point Supervision Cumulative attribute space for age and crowd density estimation

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e0791c1e-5662-46b5-8a81-8b09be051623 · outbound

This paper cites Glaston- bury, Henry Z.

Bayesian Loss for Crowd Count Estimation with Point Supervision Glaston- bury, Henry Z

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c16e2ae2-b4e8-40e1-8292-51ad8fcdee26 · outbound

This paper cites An aggregated mul- ticolumn dilated convolution network for perspective-free counting.

Bayesian Loss for Crowd Count Estimation with Point Supervision An aggregated mul- ticolumn dilated convolution network for perspective-free counting

Reference 9

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 13c1e1fb-6e65-4e7c-ac74-567d4f972ce8 · outbound

This paper cites A discriminatively trained, multiscale, deformable part model.

Bayesian Loss for Crowd Count Estimation with Point Supervision A discriminatively trained, multiscale, deformable part model

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9e605c18-ff32-4f26-b54e-6b4d16ce4587 · outbound

This paper cites Ham- precht.

Bayesian Loss for Crowd Count Estimation with Point Supervision Ham- precht

Reference 11

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 36f3840d-f8c2-4f2b-a31f-38731ac8fb64 · outbound

This paper cites an unresolved cited work.

Bayesian Loss for Crowd Count Estimation with Point Supervision Unresolved cited work

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3e71980e-3b0c-431b-a6fd-11494257b185 · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification.

Bayesian Loss for Crowd Count Estimation with Point Supervision Delving deep into rectifiers: Surpassing human-level perfor- mance on imagenet classification

Reference 13

Resolution
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Source-reported events for the cited work

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Observation f732c8df-aafb-4520-89ff-37d826131ea4 · outbound

This paper cites an unresolved cited work.

Bayesian Loss for Crowd Count Estimation with Point Supervision Unresolved cited work

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 330c1329-2e7a-407f-b463-f151de6afd2a · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Multi-source multi-scale counting in extremely dense crowd images

Reference 15

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 2f6f23f1-f3d6-46c8-972c-16392014798a · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Composition loss for counting, density map estima- tion and localization in dense crowds

Reference 16

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 75e49a83-cfcf-488a-b822-b9f8045eb229 · outbound

This paper cites Imagenet classification with deep convolutional neural net- works.

Bayesian Loss for Crowd Count Estimation with Point Supervision Imagenet classification with deep convolutional neural net- works

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 609fffaa-907a-44ab-aff8-452dba64e6fc · outbound

This paper cites Laradji, Negar Rostamzadeh, Pedro O.

Bayesian Loss for Crowd Count Estimation with Point Supervision Laradji, Negar Rostamzadeh, Pedro O

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c441ab9f-20b8-4271-91c3-c31efed1c913 · outbound

This paper cites Be- yond bags of features: Spatial pyramid matching for recog- nizing natural scene categories.

Bayesian Loss for Crowd Count Estimation with Point Supervision Be- yond bags of features: Spatial pyramid matching for recog- nizing natural scene categories

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f12263e9-9ead-41bd-a5b4-ed34bd7a7c7f · outbound

This paper cites Learning to count objects in images.

Bayesian Loss for Crowd Count Estimation with Point Supervision Learning to count objects in images

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 6067aeaf-f991-4944-93fc-47661ce4b41f · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Es- timating the number of people in crowded scenes by MID based foreground segmentation and head-shoulder detection

Reference 21

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 1026c0b7-ec2f-4aec-a7a5-753ce87376b7 · outbound

This paper cites Esti- mation of number of people in crowded scenes using per- spective transformation.

Bayesian Loss for Crowd Count Estimation with Point Supervision Esti- mation of number of people in crowded scenes using per- spective transformation

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5fb8487b-3ab9-4bc8-863c-daf05e8586bc · outbound

This paper cites Bayesian model adaptation for crowd counts.

Bayesian Loss for Crowd Count Estimation with Point Supervision Bayesian model adaptation for crowd counts

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 84eb6511-e27b-4d87-9f34-6c393e875b42 · outbound

This paper cites Hauptmann.

Bayesian Loss for Crowd Count Estimation with Point Supervision Hauptmann

Reference 24

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 98e53625-5cca-46de-b41c-ddfc4df28892 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Crowd counting using deep recurrent spatial- aware network

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 66449299-e3e4-4f41-a45d-8d5d106bb093 · outbound

This paper cites Bagdanov.

Bayesian Loss for Crowd Count Estimation with Point Supervision Bagdanov

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 1dd929f4-2670-460b-b548-ee6202f8a703 · outbound

This paper cites an unresolved cited work.

Bayesian Loss for Crowd Count Estimation with Point Supervision Unresolved cited work

Reference 27

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7251996f-082c-443a-8950-40e73c20e32e · outbound

This paper cites Keogh, and Noel E.

Bayesian Loss for Crowd Count Estimation with Point Supervision Keogh, and Noel E

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 8963abe8-6eec-42c2-bfe3-f03abf4868c9 · outbound

This paper cites Nathan Mundhenk, Goran Konjevod, Wesam A.

Bayesian Loss for Crowd Count Estimation with Point Supervision Nathan Mundhenk, Goran Konjevod, Wesam A

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9a38072e-6732-450e-8694-c68da224ba32 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision To- wards perspective-free object counting with deep learning

Reference 30

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 71a76d66-84cd-47a1-9494-07f530cc6299 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision COUNT forest: Co-voting uncertain number of targets using random forest for crowd density estimation

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation c4424107-c78d-4d2f-a90e-d8f58903cd4b · outbound

This paper cites Iterative crowd counting.

Bayesian Loss for Crowd Count Estimation with Point Supervision Iterative crowd counting

Reference 32

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation d39c3cf2-4231-4f4c-81d4-3831f07c8ab0 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 33

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 50966c1d-5f4c-4629-a4e5-dae9dc44b16e · outbound

This paper cites an unresolved cited work.

Bayesian Loss for Crowd Count Estimation with Point Supervision Unresolved cited work

Reference 34

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raw_fallback, observed 2026-08-14T14:14:58.369554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.706543Z digest=sha256:5f730500fb3632dc056a17330c03b25dcd697c160e825a6836cef802886b64dc

Observation 1c8600c0-084d-46a0-9943-7895daad5b24 · outbound

This paper cites Crowd counting using multiple local features.

Bayesian Loss for Crowd Count Estimation with Point Supervision Crowd counting using multiple local features

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.353318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.711637Z digest=sha256:69dd9718da55be17d396f58c5063224e50a3157d9aaa83dc0bf1dba63fbea2f0

Observation 541aaeb6-f7ea-4b02-938e-345e67e7631f · outbound

This paper cites End-to-end crowd counting via joint learning local and global count.

Bayesian Loss for Crowd Count Estimation with Point Supervision End-to-end crowd counting via joint learning local and global count

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.336925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.718076Z digest=sha256:cd87ad08db747522d4a882b7dee7ad7b5d7cf05e2c71391b05344783f5f28627

Observation 727e5c7f-5650-4734-a317-a3ed7d9e4980 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Crowd counting via adversarial cross-scale consistency pursuit

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.319276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.724046Z digest=sha256:0408b93f77c80c718a39d37a05d88376cd87fd725c8f5f11eee3b6e6175a0f93

Observation f892eb77-5515-4d43-839b-5b06861f6ce9 · outbound

This paper cites Crowd counting with deep negative correlation learning.

Bayesian Loss for Crowd Count Estimation with Point Supervision Crowd counting with deep negative correlation learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.302156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.730046Z digest=sha256:70eb954c9933a95108265169e2aefdd613f6b36c70d4e7b563be34fe1abbf5cd

Observation e45f3b72-093f-4094-8d28-77d9a1033296 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-14T14:14:57.736721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T14:14:57.736721Z digest=sha256:7442b32f0a4a9980cdecd3f0299e6cfd71679f5eb08c50de32633cbfa3080eda

Observation e8871318-ffa7-4d01-a60a-684ecca0c7c9 · outbound

This paper cites Sindagi and Vishal M.

Bayesian Loss for Crowd Count Estimation with Point Supervision Sindagi and Vishal M

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.286018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.743407Z digest=sha256:8302078b15f2e7588d61ed29b07fac66874c6bb0728175adfe36da51c4dee949

Observation ec1d1dbf-f913-43c2-8921-5f2162c3534e · outbound

This paper cites Sindagi and Vishal M.

Bayesian Loss for Crowd Count Estimation with Point Supervision Sindagi and Vishal M

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.270312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.748915Z digest=sha256:54c803b24dd2f2c737ca393ebc384ab19af61cc75b4910f5d52b4154b2c26680

Observation 4b4e0401-3b5b-4601-8314-54da6fd83282 · outbound

This paper cites an unresolved cited work.

Bayesian Loss for Crowd Count Estimation with Point Supervision Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-14T14:14:58.253490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.753691Z digest=sha256:13368c7ff4ea4bc19a1a6a31097477cddddbb74ba90503ba67afc6cd17cc7bd6

Observation 8b215bc6-17d3-4fce-bedd-14869ed07d79 · outbound

This paper cites an unresolved cited work.

Bayesian Loss for Crowd Count Estimation with Point Supervision Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-14T14:14:58.237478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.758543Z digest=sha256:17b78430ffadb34de3845c84819c77caf3221286e713647f00909fd3261b8fd5

Observation 5a150c40-a477-4054-88af-ac8a46e659e0 · outbound

This paper cites Rao, Kumar T.

Bayesian Loss for Crowd Count Estimation with Point Supervision Rao, Kumar T

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.219152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.765418Z digest=sha256:2769c6247016e277b1fb0d1232e57a693d9bb6e9c05d61cd10140445a3f39ec2

Observation bf201318-8ea3-4bda-9f7f-c3a98e93e6ae · outbound

This paper cites Learning to count with CNN boosting.

Bayesian Loss for Crowd Count Estimation with Point Supervision Learning to count with CNN boosting

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.202851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.770502Z digest=sha256:e5ef325d2a6a18e0a90437415cef2c68d463989473ca5b6f6f8e26dbe625b36d

Observation bf39cf13-879d-4255-a617-565df28e74f8 · outbound

This paper cites Deep people counting in extremely dense crowds.

Bayesian Loss for Crowd Count Estimation with Point Supervision Deep people counting in extremely dense crowds

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.186445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.776885Z digest=sha256:7e9e3dbbe6ed2e90af7559caeeb0c03f3c8f46ad9e9fe3441a0a8c596d6aefd1

Observation 6a688a98-cda0-4b7d-9928-977565e01871 · outbound

This paper cites Locality-constrained linear cod- ing for image classification.

Bayesian Loss for Crowd Count Estimation with Point Supervision Locality-constrained linear cod- ing for image classification

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.170493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.782451Z digest=sha256:c11249c972fdf210aa4f498731d0b57d55d10d01b93acb3c03d088963bf89bfd

Observation 3879c59e-7c80-45a9-a050-1dc1aee15b0d · outbound

This paper cites Repulsion loss: Detecting pedestri- ans in a crowd.

Bayesian Loss for Crowd Count Estimation with Point Supervision Repulsion loss: Detecting pedestri- ans in a crowd

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.154755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.787352Z digest=sha256:db461f03cf4721143042a4faf06e719c5a1aa814fdfbc9627ec98cda8e158e1a

Observation 62d9776e-d4d5-4938-b863-ad89bddd38d6 · outbound

This paper cites Grassmann pooling as compact homoge- neous bilinear pooling for fine-grained visual classification.

Bayesian Loss for Crowd Count Estimation with Point Supervision Grassmann pooling as compact homoge- neous bilinear pooling for fine-grained visual classification

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.137472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.792220Z digest=sha256:d2f6729036c104b7197f226c0bd5afea38dc06a84db0aa81b08628e03d25535e

Observation 5abcb4a1-7b17-4245-925f-184dce515cf6 · outbound

This paper cites Kernelized subspace pooling for deep local descriptors.

Bayesian Loss for Crowd Count Estimation with Point Supervision Kernelized subspace pooling for deep local descriptors

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.120323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.797413Z digest=sha256:594701586e8d0cd9098eaddbe5902066e26787d378fbbbe1c64c57e602c6474f

Observation 9be29f74-5a1c-463b-ad52-15b87fd2b6c8 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Spatiotem- poral modeling for crowd counting in videos

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.103115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.802395Z digest=sha256:57e3531e48d431ab526bee9f57771c6ed289890a1e67a453d04a107e7f097183

Observation 0dad8fcf-2220-4133-a2e0-7ab5e71c9d47 · outbound

This paper cites Structured model- ing of joint deep feature and prediction refinement for salient object detection.

Bayesian Loss for Crowd Count Estimation with Point Supervision Structured model- ing of joint deep feature and prediction refinement for salient object detection

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.085377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.807442Z digest=sha256:31f7768535191c6b704e7e3bb6f593db7a7a36ebd75fc5d4b8a9c9fc2ae029ab

Observation 0f7a590b-2f53-4e02-852a-739f8da50a07 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Cross-scene crowd counting via deep convolutional neural networks

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.068148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.812348Z digest=sha256:1c1086617bcd665c54b3c639442d13d7306f2b5783072e2d7e2b6ca9cce082a6

Observation e3d6fb8b-2a27-4906-8ea4-fc7b9bda5c08 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Crowd counting via scale-adaptive convolutional neural network

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.050009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.817196Z digest=sha256:6ceab9c2abf18491f063fb6b2edac76e2d35263b0a7dd721256e9e05f4e6ce8c

Observation 88f9d5b8-2d8f-402f-8888-933a416d2db0 · outbound

This paper cites an unresolved cited work.

Bayesian Loss for Crowd Count Estimation with Point Supervision Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-14T14:14:58.031667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.823390Z digest=sha256:4cfcfb6aa1fde66a288b112a717e5046ab8e33c32d61c477acd085b00a0b1cd6

Observation e40e95d4-fc2c-4f15-8e16-f034f683c612 · outbound

This paper cites Costeira, and Jose M.

Bayesian Loss for Crowd Count Estimation with Point Supervision Costeira, and Jose M

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:58.012162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.828900Z digest=sha256:0b6d7f9f2e85a42044dd4e2aae3f5d14c51174f46e18bc7886b6f1567432fbfe

Observation db95fead-d108-47cb-a488-9da499941442 · outbound

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

Bayesian Loss for Crowd Count Estimation with Point Supervision Single-image crowd counting via multi-column convolutional neural network

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:57.989383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.833753Z digest=sha256:bdd1dd9e526a38b57dc4e5793bb1f0c3d90fb207ea71714be11c56b983a00858

Observation 93688924-bdfc-4802-8e5c-75b4160c96ef · outbound

This paper cites Bayesian human segmen- tation in crowded situations.

Bayesian Loss for Crowd Count Estimation with Point Supervision Bayesian human segmen- tation in crowded situations

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:57.969206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.839171Z digest=sha256:ead2aa7922bd01704530cecb421fe323af02c44f822b58541a1c9d0327ebeca6

Observation a8f4cae6-3825-4dd7-909a-eaa94446fdea · outbound

This paper cites Crossing-line crowd counting with two-phase deep neural networks.

Bayesian Loss for Crowd Count Estimation with Point Supervision Crossing-line crowd counting with two-phase deep neural networks

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:57.950721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.843804Z digest=sha256:514b488ee0fa2c98debd913e371bc47b476d4e66bd17a3337a60b04585f353ee

Observation 400c3be3-8e93-406b-8430-21602d2601bd · outbound

This paper cites Discriminative fea- ture learning with foreground attention for person re- identification.

Bayesian Loss for Crowd Count Estimation with Point Supervision Discriminative fea- ture learning with foreground attention for person re- identification

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:57.933838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.849324Z digest=sha256:244783d0579e5228b826e454bc23670ae485850475851c07b2acfddfda0e177c

Observation eb257311-9e09-4761-b3fa-411c917509b5 · outbound

This paper cites Point to set similarity based deep fea- ture learning for person re-identification.

Bayesian Loss for Crowd Count Estimation with Point Supervision Point to set similarity based deep fea- ture learning for person re-identification

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T14:14:57.916153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-14T14:14:57.854352Z digest=sha256:04b84f86af75ae0b988d74c6db13d1a267bba04e98a9bc1fe5de396d5e6e78eb

Pith citing papers

No inbound Pith citation observations are available.