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Paper Citation Record · LEDGER

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review

As of 20 August 2026, this Paper Citation Record lists 100 of 193 outbound references and 0 inbound Pith citation observations for arXiv:2505.18401.

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

pith.paper-citation-record.v1
2505.18401 v1

Coverage vector

measured 100 of 193 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:35:25.973511Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

100 of 193 outbound references displayed

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  • verified fuzzy0
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Outbound references

Observation 5d0fee5c-3457-44b4-8215-8b90bd820471 · outbound

This paper cites Social lstm: Human trajectory prediction in crowded spaces.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Social lstm: Human trajectory prediction in crowded spaces

Reference 1

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Observation aae4858f-e619-41b7-98a3-eb2052b5a118 · outbound

This paper cites Social ways: Learning multi-modal distributions of pedestrian trajectories with gans.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Social ways: Learning multi-modal distributions of pedestrian trajectories with gans

Reference 2

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Observation 594cc9ca-56a7-4bd4-88f8-b8327f85cce3 · outbound

This paper cites Context-aware trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Context-aware trajectory prediction

Reference 3

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Observation 9238ed61-e26c-498f-921b-7003bc33fdcd · outbound

This paper cites Crowd characterization in surveillance videos using deep-graph convolutional neural network.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Crowd characterization in surveillance videos using deep-graph convolutional neural network

Reference 4

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Observation c617f309-6eee-4f6d-b742-ca3b2739398b · outbound

This paper cites Understanding crowd flow patterns using active-langevin model.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Understanding crowd flow patterns using active-langevin model

Reference 5

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Observation 7e085cdc-98a2-4ae1-aacc-035a2176a256 · outbound

This paper cites Characterization of orderly behavior of human crowd in videos using deep learning.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Characterization of orderly behavior of human crowd in videos using deep learning

Reference 6

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Observation 77466ca5-05dc-40f1-a721-d8635d63950d · outbound

This paper cites Pidlnet: A physics-induced deep learning network for characterization of crowd videos.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Pidlnet: A physics-induced deep learning network for characterization of crowd videos

Reference 7

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Observation 7e16e5e2-e939-43da-b911-e2f81a677629 · outbound

This paper cites Ensemble classification of video-recorded crowd movements.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Ensemble classification of video-recorded crowd movements

Reference 8

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Observation fbd6d0b2-1f40-4480-9755-46da01cc8883 · outbound

This paper cites Group lstm: Group trajectory prediction in crowded scenarios.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Group lstm: Group trajectory prediction in crowded scenarios

Reference 9

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Observation 272dde20-a404-486c-92e8-2e5a3610d6d8 · outbound

This paper cites Embedding group and obstacle information in lstm networks for human trajectory prediction in crowded scenes.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Embedding group and obstacle information in lstm networks for human trajectory prediction in crowded scenes

Reference 10

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Observation ce2494d6-015a-4f97-8f92-3c64534b856e · outbound

This paper cites An introduction to the kalman filter.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review An introduction to the kalman filter

Reference 11

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Observation 039d1764-6caf-4dcc-90b6-896308369ebe · outbound

This paper cites Latent dirichlet allocation.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Latent dirichlet allocation

Reference 12

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Observation 2b9d12c5-fe81-4e8e-bb36-91d8cda5b7ab · outbound

This paper cites A short review of deep learning methods for understanding group and crowd activities.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review A short review of deep learning methods for understanding group and crowd activities

Reference 13

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Observation d0fdf595-7e82-4244-a53e-e1fdcc3f00c6 · outbound

This paper cites Pedestrian models for autonomous driving part ii: high-level models of human behavior.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Pedestrian models for autonomous driving part ii: high-level models of human behavior

Reference 14

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This paper cites Quo vadis, action recognition? a new model and the kinetics dataset.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Quo vadis, action recognition? a new model and the kinetics dataset

Reference 15

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Observation 1d8f5083-7afb-4859-a107-9025c98ab65a · outbound

This paper cites Fight detection with spatial and channel wise attention-based convlstm model.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Fight detection with spatial and channel wise attention-based convlstm model

Reference 16

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Observation 3c2c332b-0ba0-4e25-be4e-c8580026e794 · outbound

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

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs

Reference 17

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Observation 9d1190e1-3eda-4875-9be8-b2929e2829e1 · outbound

This paper cites Neural ordinary differential equations.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Neural ordinary differential equations

Reference 18

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Observation 199336b8-0fa6-434f-ae3f-bf4b345e4e8a · outbound

This paper cites Multimodal pedestrian trajectory prediction using probabilistic proposal network.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Multimodal pedestrian trajectory prediction using probabilistic proposal network

Reference 19

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Observation 16c9cc78-42f1-4000-b153-a9ae9b9a48cc · outbound

This paper cites Infogan: Interpretable representation learning by information maximizing generative adversarial nets.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Infogan: Interpretable representation learning by information maximizing generative adversarial nets

Reference 20

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Observation ee74a36c-68a9-4a3d-b2d3-3bee4a045c42 · outbound

This paper cites Three-dimensional atrous inception module for crowd behavior classification.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Three-dimensional atrous inception module for crowd behavior classification

Reference 21

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This paper cites A unified framework for multi-target tracking and collective activity recognition.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review A unified framework for multi-target tracking and collective activity recognition

Reference 22

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Observation f5326511-1058-41fa-8b02-f31d71943730 · outbound

This paper cites What are they doing?: Collective activity classification using spatio-temporal relationship among people.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review What are they doing?: Collective activity classification using spatio-temporal relationship among people

Reference 23

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Empirical evaluation of gated recurrent neural networks on sequence modeling

Reference 24

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Observation 9bf94cbf-668c-446f-b340-3f7146f5d084 · outbound

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review A recurrent latent variable model for sequential data

Reference 25

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Observation a5922077-1bde-4f61-b656-4f730726c3a9 · outbound

This paper cites Social-vrnn: One-shot multi-modal trajectory prediction for interacting pedestrians.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Social-vrnn: One-shot multi-modal trajectory prediction for interacting pedestrians

Reference 26

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Observation 94f7ec9c-7260-4ddb-a711-b61373a96260 · outbound

This paper cites Behavior recognition based on category subspace in crowded videos.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Behavior recognition based on category subspace in crowded videos

Reference 27

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 28

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Modelling pedestrian trajectory patterns with gaussian processes

Reference 29

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Observation 4e94aa21-683b-4dd9-8020-6d275d1bc27d · outbound

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review The ensemble kalman filter: Theoretical formulation and practical implementation

Reference 30

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This paper cites Citymomentum: an online approach for crowd behavior prediction at a citywide level.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Citymomentum: an online approach for crowd behavior prediction at a citywide level

Reference 31

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Fundamentals of neural networks: architectures, algorithms, and applications, 1994

Reference 32

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Forward propagation of a push through a row of people

Reference 33

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This paper cites Soft+ hardwired attention: An lstm framework for human trajectory prediction and abnormal event detection.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Soft+ hardwired attention: An lstm framework for human trajectory prediction and abnormal event detection

Reference 34

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Markov models and hidden M arkov models: A brief tutorial

Reference 35

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This paper cites Spatio-temporal attention transformer model for future trajectory forecast.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Spatio-temporal attention transformer model for future trajectory forecast

Reference 36

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Transformer networks for trajectory forecasting

Reference 37

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Observation 405d4f77-799d-4618-8cd2-c4f72c0185cd · outbound

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Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Continuum modeling of crowd turbulence

Reference 38

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Observation fd725c8d-5dae-49bc-94eb-a3f9264b81e0 · outbound

This paper cites Resolving collisions in dense 3d crowd animations.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Resolving collisions in dense 3d crowd animations

Reference 39

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Observation d4651404-021e-4dc1-a96e-06424fcbab6a · outbound

This paper cites Generative adversarial nets.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Generative adversarial nets

Reference 40

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Observation d1285cc4-7747-4b1b-871c-cecf26436d63 · outbound

This paper cites Stochastic trajectory prediction via motion indeterminacy diffusion.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Stochastic trajectory prediction via motion indeterminacy diffusion

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Observation c48a8cec-ca34-4bd7-a453-1f4f0e391818 · outbound

This paper cites Social gan: Socially acceptable trajectories with generative adversarial networks.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Social gan: Socially acceptable trajectories with generative adversarial networks

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Observation 4fceb606-b8c8-4a8d-a32f-2e2de59b5204 · outbound

This paper cites Guy, Jur van den Berg, Wenxi Liu, Rynson Lau, Ming C.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Guy, Jur van den Berg, Wenxi Liu, Rynson Lau, Ming C

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Observation 1a68db03-7e90-4d1a-93fd-6d21ec572813 · outbound

This paper cites A Survey on Visual Transformer.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review A Survey on Visual Transformer

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Observation 056aad40-30ba-4dbb-b0df-7eab384a81e3 · outbound

This paper cites Learning spatio-temporal features with 3d residual networks for action recognition.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Learning spatio-temporal features with 3d residual networks for action recognition

Reference 45

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Observation d8ccdc0c-917a-4111-9ec9-c735f37c3cc5 · outbound

This paper cites Informative scene decomposition for crowd analysis, comparison and simulation guidance.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Informative scene decomposition for crowd analysis, comparison and simulation guidance

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Observation ee866f90-9f89-49d2-8fe8-34d05ad70c2f · outbound

This paper cites Learning Extremely High Density Crowds as Active Matters.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Learning Extremely High Density Crowds as Active Matters

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local_arxiv, observed 2026-08-07T14:35:26.622793Z

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Observation 2aca5d50-3a49-4db4-a909-6149e7a38b0a · outbound

This paper cites Deep residual learning for image recognition.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Deep residual learning for image recognition

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Observation 0255fbce-5ae1-4947-9201-e1ee68382453 · outbound

This paper cites Social force model for pedestrian dynamics.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Social force model for pedestrian dynamics

Reference 49

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source=arxiv_source observed=2026-08-07T14:35:25.767600Z digest=sha256:6d5a6de903712012e55d2bc20b9c7ca37c9092b4308233800b14b5a125502b59

Observation 0944b726-21f1-4b1e-b802-b8cc0fc829aa · outbound

This paper cites Long short-term memory.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Long short-term memory

Reference 50

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Observation dcb75dd0-05e9-48fb-b42b-fc5b25bdf03f · outbound

This paper cites Approximation capabilities of multilayer feedforward networks.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Approximation capabilities of multilayer feedforward networks

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Observation 4fc0a8ef-5d42-44a1-aaa0-3b3275855b45 · outbound

This paper cites Multilayer feedforward networks are universal approximators.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Multilayer feedforward networks are universal approximators

Reference 52

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source=arxiv_source observed=2026-08-07T14:35:25.779616Z digest=sha256:2938300514788a4f473a8989d6a69680fabc7631b3c36fe2e584fb7bfe83a9d9

Observation c6167387-2fa9-4113-ba46-f1b9d6a1741a · outbound

This paper cites Stgat: Modeling spatial-temporal interactions for human trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Stgat: Modeling spatial-temporal interactions for human trajectory prediction

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Observation 62e80fb9-7f29-498a-b2b6-99d1df18daa7 · outbound

This paper cites A continuum theory for the flow of pedestrians.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review A continuum theory for the flow of pedestrians

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Observation 85d7ca3e-2afb-4d1c-a01f-5e85d47bf287 · outbound

This paper cites Interpretable self-aware neural networks for robust trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Interpretable self-aware neural networks for robust trajectory prediction

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source=arxiv_source observed=2026-08-07T14:35:25.791622Z digest=sha256:055345be63fd8b2a41b4c2b1386e0bd8a6bea1c0075b0cf32520c51de9e7a549

Observation 3e548e5a-5a32-4bd0-b070-a34eacf3b680 · outbound

This paper cites Discrete residual flow for probabilistic pedestrian behavior prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Discrete residual flow for probabilistic pedestrian behavior prediction

Reference 56

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source=arxiv_source observed=2026-08-07T14:35:25.795391Z digest=sha256:3b7dac2c1c38b60a5f0764cb220eb9c3380d578a598154182c9f16711ee1f0c3

Observation 7370236e-dd53-4c6a-a889-9597d070eb2e · outbound

This paper cites The material point method for simulating continuum materials.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review The material point method for simulating continuum materials

Reference 57

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source=arxiv_source observed=2026-08-07T14:35:25.799070Z digest=sha256:9e99159bccc2629d4167205d284689e80d7f8865425fa40e132097ed41827b45

Observation 97c9472e-dee9-4932-8ec5-baf4533ae98e · outbound

This paper cites Deepcrowd: A deep model for large-scale citywide crowd density and flow prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Deepcrowd: A deep model for large-scale citywide crowd density and flow prediction

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source=arxiv_source observed=2026-08-07T14:35:25.803616Z digest=sha256:9705d1c41bd39aa06f3fb77026045c5d7f99915a5be928091e7873b6a296be6b

Observation 701e6611-eb65-4d75-8cbf-7cf1b205ce2a · outbound

This paper cites Crowd behavior recognition using dense trajectories.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Crowd behavior recognition using dense trajectories

Reference 59

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source=arxiv_source observed=2026-08-07T14:35:25.807968Z digest=sha256:1fc98b0710e7fed60d0530af9b13d5f27222178e15dcc7c8e0018ec0dc3a9221

Observation f9200720-592c-4b09-9d06-50b0421f1e45 · outbound

This paper cites On neural differential equations.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review On neural differential equations

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source=arxiv_source observed=2026-08-07T14:35:25.812227Z digest=sha256:5ee191aecc17e95055670c59df12f7cc33c39bc6245250284537b265faa60482

Observation 14fcc052-ce26-4a5d-8efa-7141bc75690a · outbound

This paper cites Brvo: Predicting pedestrian trajectories using velocity-space reasoning.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Brvo: Predicting pedestrian trajectories using velocity-space reasoning

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source=arxiv_source observed=2026-08-07T14:35:25.816019Z digest=sha256:1734e46828af16f201fe8dcfd5b054cd58b3a9c45846bb1ff3a41c9266c330c4

Observation 8c5bf643-e4d1-4c50-8019-d7ebb1be08f2 · outbound

This paper cites Auto-Encoding Variational Bayes.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Auto-Encoding Variational Bayes

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source=arxiv_source observed=2026-08-07T14:35:25.820026Z digest=sha256:49639f100d174040d2fa1342f94e6605798aa2cdbd777546d6ec2f353eafb106

Observation 3e162658-a2fb-4e93-b222-7b837e35237f · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Semi-Supervised Classification with Graph Convolutional Networks

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source=arxiv_source observed=2026-08-07T14:35:25.824151Z digest=sha256:90b6c88b45bf9e9f0ac7c88fd9445587ff25627b9093e1a87005d1e602e46525

Observation dcd424b8-5705-477f-a712-9376e42eced3 · outbound

This paper cites Activity forecasting.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Activity forecasting

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source=arxiv_source observed=2026-08-07T14:35:25.828580Z digest=sha256:66f2b138490c6a29e396949de3bb17523f5b4621fa44958e7cc446018e7c17f7

Observation e1619c0c-e134-4a0a-a008-b2c3107bc133 · outbound

This paper cites Crowd behavior analysis: A review where physics meets biology.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Crowd behavior analysis: A review where physics meets biology

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source=arxiv_source observed=2026-08-07T14:35:25.832493Z digest=sha256:da4dfa46327612fbf323415f1f5a5ff949a3f70012c0ee8cad0cf2acf29fbb63

Observation 7f9e5da5-be8a-4362-ac39-4e5b3d436f5e · outbound

This paper cites Social-bigat: Multimodal trajectory forecasting using bicycle-gan and graph attention networks.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Social-bigat: Multimodal trajectory forecasting using bicycle-gan and graph attention networks

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source=arxiv_source observed=2026-08-07T14:35:25.836901Z digest=sha256:7f87639fb28ca56e9ab34bf7a40a190269e0fa05274274b2e1117e56339628d2

Observation 8140a34a-033f-4807-b345-621a103d42c3 · outbound

This paper cites Handwritten digit recognition with a back-propagation network.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Handwritten digit recognition with a back-propagation network

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source=arxiv_source observed=2026-08-07T14:35:25.841429Z digest=sha256:fb4fab1fee60719527cc97ea4fdb7d3a9bc33c6c8967c70ac33dcef6224d816e

Observation 3b58cd85-e251-4899-aa55-c1b80482459b · outbound

This paper cites Muse-vae: Multi-scale vae for environment-aware long term trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Muse-vae: Multi-scale vae for environment-aware long term trajectory prediction

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Observation 14f7ded9-0446-47e5-8237-1712548e9ace · outbound

This paper cites Crowds by example.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Crowds by example

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Observation 1e0b6fa3-2e74-468a-987c-887017ca3bc9 · outbound

This paper cites Graph-based spatial transformer with memory replay for multi-future pedestrian trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Graph-based spatial transformer with memory replay for multi-future pedestrian trajectory prediction

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source=arxiv_source observed=2026-08-07T14:35:25.853137Z digest=sha256:e60817f49991da0b6105003ec457727fea5e7f2a339db5ab729258ff1d084c21

Observation e4ec1ee7-f20c-4b90-9a4b-206bf3f91bb0 · outbound

This paper cites A deep spatiotemporal perspective for understanding crowd behavior.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review A deep spatiotemporal perspective for understanding crowd behavior

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source=arxiv_source observed=2026-08-07T14:35:25.856983Z digest=sha256:0a3864d256287bee8a9ba1f35aac540187aba7a83384abfb53313bfbdd698391

Observation 3c5f6887-21bd-4d69-a1a7-08f271037bad · outbound

This paper cites Ptp-stgcn: pedestrian trajectory prediction based on a spatio-temporal graph convolutional neural network.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Ptp-stgcn: pedestrian trajectory prediction based on a spatio-temporal graph convolutional neural network

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Observation 1e349869-2567-457d-a107-1cb7e3e9cab6 · outbound

This paper cites Peeking into the future: Predicting future person activities and locations in videos.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Peeking into the future: Predicting future person activities and locations in videos

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source=arxiv_source observed=2026-08-07T14:35:25.864826Z digest=sha256:6e68c63fdcb7c52a04efd779551381bc674ea6ca97dbcf7cdc6498d1c20dda01

Observation c785ccf9-2fb7-40cd-a252-c7126a7817bd · outbound

This paper cites Progressive pretext task learning for human trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Progressive pretext task learning for human trajectory prediction

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Observation dde3942e-c1f1-4715-b971-c0b7c3089993 · outbound

This paper cites Intention-aware denoising diffusion model for trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Intention-aware denoising diffusion model for trajectory prediction

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Observation c6fceed4-ad11-405a-85a2-61618bed15ba · outbound

This paper cites Multimodal-semantic context-aware graph neural network for group activity recognition.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Multimodal-semantic context-aware graph neural network for group activity recognition

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source=arxiv_source observed=2026-08-07T14:35:25.877207Z digest=sha256:180636c05a1b1e593f4c08d432abccf4327ea94b6fa946c15b96987a7b4600cc

Observation 9782ca77-a895-474c-b396-8d5d5aee94fc · outbound

This paper cites Visual-semantic graph neural network with pose-position attentive learning for group activity recognition.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Visual-semantic graph neural network with pose-position attentive learning for group activity recognition

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source=arxiv_source observed=2026-08-07T14:35:25.881276Z digest=sha256:fe0fbf6136c778793a9bf9b7021f97744ec1f6b26c06af9a056c07b4ae222811

Observation 9d327706-a7f8-481d-a3b0-0f2e8a4a7fdf · outbound

This paper cites Attention-aware social graph transformer networks for stochastic trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Attention-aware social graph transformer networks for stochastic trajectory prediction

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source=arxiv_source observed=2026-08-07T14:35:25.885225Z digest=sha256:772e5852dc1e181194f8dd719a5897b766d9e7fa51a38f5c6e44507b819de73e

Observation c7be628e-5249-445c-801e-3ebb0d019d1c · outbound

This paper cites Knowledge-aware graph transformer for pedestrian trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Knowledge-aware graph transformer for pedestrian trajectory prediction

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source=arxiv_source observed=2026-08-07T14:35:25.889876Z digest=sha256:e78d4c1448d91a7c286368b9640ee1a94ec78e1b7ec11d8df32b62b1cf009283

Observation eccf7ac5-c13e-4509-978b-cccc3611b648 · outbound

This paper cites Video swin transformer.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Video swin transformer

Reference 80

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source=arxiv_source observed=2026-08-07T14:35:25.893828Z digest=sha256:7b3e4b2cdb8bb671a842d4791b7a32d5a8ebb9bc5c3f2717f6875d7e81338f93

Observation 792b02ea-bffa-467c-ac0a-ec2e61b68101 · outbound

This paper cites Graphic-graph-based representation for analyzing people’s high-level interactions in crowds.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Graphic-graph-based representation for analyzing people’s high-level interactions in crowds

Reference 81

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source=arxiv_source observed=2026-08-07T14:35:25.897741Z digest=sha256:457f5cc5a7b94e7e5847f3e508c0740873bcd44df990fabd8cbe54e793bbde79

Observation 0aaffdeb-4398-4f84-abfc-2e1d8e71cd9a · outbound

This paper cites Agent-based human behavior modeling for crowd simulation.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Agent-based human behavior modeling for crowd simulation

Reference 82

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source=arxiv_source observed=2026-08-07T14:35:25.901716Z digest=sha256:f0a1b9db8ecdd0c088467d4dce2ca07b4c7a39af24da28bd20a91aad13ca6851

Observation 3aa0b813-ecc7-4339-b04d-b741f1f559ca · outbound

This paper cites Introduction to gaussian processes.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Introduction to gaussian processes

Reference 83

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source=arxiv_source observed=2026-08-07T14:35:25.905985Z digest=sha256:290ff9092195bcaa3fade85bb43d820183388d560da8388d3312c3e530576285

Observation eb983051-b67b-472e-85e8-37a33eb407c0 · outbound

This paper cites Deep residual network with subclass discriminant analysis for crowd behavior recognition.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Deep residual network with subclass discriminant analysis for crowd behavior recognition

Reference 84

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source=arxiv_source observed=2026-08-07T14:35:25.910046Z digest=sha256:b3853f0adef9159d276bb13f90168592c0ba92acc8435ae29b60b9492f4099be

Observation 59f49e9f-8c85-4c21-ac4b-71b71649358e · outbound

This paper cites It is not the journey but the destination: Endpoint conditioned trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review It is not the journey but the destination: Endpoint conditioned trajectory prediction

Reference 85

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source=arxiv_source observed=2026-08-07T14:35:25.914378Z digest=sha256:46f8409fbc7eb74ec2114e55b7e497dfd9a17d8c855cd51d12acfd7399cfdaab

Observation 718e054e-2fe2-4ec1-89c7-4f962e1cdb0d · outbound

This paper cites Leapfrog diffusion model for stochastic trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Leapfrog diffusion model for stochastic trajectory prediction

Reference 86

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source=arxiv_source observed=2026-08-07T14:35:25.918286Z digest=sha256:599ff801ecec01ddc0e1cf6e8f115f5e21147cc49d3fdac57c23ec2e82bf240c

Observation 43983377-d2e3-4e91-8d9a-00cc01ca70bf · outbound

This paper cites A new approach to dominant motion pattern recognition at the macroscopic crowd level.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review A new approach to dominant motion pattern recognition at the macroscopic crowd level

Reference 87

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source=arxiv_source observed=2026-08-07T14:35:25.922233Z digest=sha256:d0d0d4b28e499191a930e908973564f2864efc5942c62aa810dcb3736755f0f2

Observation 4fad6e52-5414-46de-ab74-8cc64c226c00 · outbound

This paper cites Pi-neugode: Physics-informed graph neural ordinary differential equations for spatiotemporal trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Pi-neugode: Physics-informed graph neural ordinary differential equations for spatiotemporal trajectory prediction

Reference 88

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source=arxiv_source observed=2026-08-07T14:35:25.926145Z digest=sha256:5e936a01ba7161be01af5ea8ebee2bdcb83107a3f9f623db818d2cc763414da6

Observation 6bac9fbf-4bf6-47a1-87cc-9c5188119e2b · outbound

This paper cites Social-stgcnn: A social spatio-temporal graph convolutional neural network for human trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Social-stgcnn: A social spatio-temporal graph convolutional neural network for human trajectory prediction

Reference 89

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source=arxiv_source observed=2026-08-07T14:35:25.930047Z digest=sha256:70a5a49bfe9e2c3cbd5e9fff92cbaa7a0cc626b9f143f3a999869070bad35989

Observation 5a05e283-4840-4dcc-8ed1-40e7b4c8efba · outbound

This paper cites Dag-net: Double attentive graph neural network for trajectory forecasting.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Dag-net: Double attentive graph neural network for trajectory forecasting

Reference 90

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source=arxiv_source observed=2026-08-07T14:35:25.934203Z digest=sha256:87d2d861a9e9ef9aa9058fed61361be47507a5e06cd5db0f945b5aa57cf7af93

Observation 41b808a6-d2d6-4cfd-a061-ba0445a802db · outbound

This paper cites The group and crowd analysis interdisciplinary challenge.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review The group and crowd analysis interdisciplinary challenge

Reference 91

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source=arxiv_source observed=2026-08-07T14:35:25.938209Z digest=sha256:cf79432e17b7262a8fd03d02f050a06313a8552dfb3b196260475c0b6bf501d9

Observation 44ae922e-1e8e-4b83-bf30-c7e3a693da0c · outbound

This paper cites Convolutional neural network for trajectory prediction.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Convolutional neural network for trajectory prediction

Reference 92

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source=arxiv_source observed=2026-08-07T14:35:25.942232Z digest=sha256:d9068d52e413400656a72531bb554ca65fb0012e7ad6acaf353f6a70c8f19b72

Observation b0166f7d-bf5b-4be8-aaeb-d5c769f10b22 · outbound

This paper cites You'll never walk alone: Modeling social behavior for multi-target tracking.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review You'll never walk alone: Modeling social behavior for multi-target tracking

Reference 93

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source=arxiv_source observed=2026-08-07T14:35:25.945991Z digest=sha256:e19a96fecb082dd31c0b40b789bb1b05e07ab469786bf10903bc6b02f758ee33

Observation 76999736-803f-404c-974f-16cc490a6315 · outbound

This paper cites G tv-l1 optical flow estimation image process.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review G tv-l1 optical flow estimation image process

Reference 94

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source=arxiv_source observed=2026-08-07T14:35:25.949949Z digest=sha256:0dd7caed274896d2351cea4df613690308d730ba07d5e86836c908c758f73817

Observation 1518078c-a046-42a9-a29d-07920a77c695 · outbound

This paper cites Crowd behavior detection: leveraging video swin transformer for crowd size and violence level analysis.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Crowd behavior detection: leveraging video swin transformer for crowd size and violence level analysis

Reference 95

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source=arxiv_source observed=2026-08-07T14:35:25.953675Z digest=sha256:90c27ee68440c57b583e901df7ea735dca8845033734d38e60b6c40a493f5246

Observation 8c1fccfc-4d80-4f48-b168-2b24f723242d · outbound

This paper cites Autonomous vehicles that interact with pedestrians: A survey of theory and practice.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Autonomous vehicles that interact with pedestrians: A survey of theory and practice

Reference 96

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source=arxiv_source observed=2026-08-07T14:35:25.957911Z digest=sha256:49beb192a5f5cf2b88d64d4252d74331b5aa0a7d4be5fd471a1dc5aa492b6d27

Observation 38d2d6b3-3bbc-4a12-9ec7-01a213e39bb1 · outbound

This paper cites Real-time crowd behavior recognition in surveillance videos based on deep learning methods.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Real-time crowd behavior recognition in surveillance videos based on deep learning methods

Reference 97

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source=arxiv_source observed=2026-08-07T14:35:25.961858Z digest=sha256:00f293b7beeae317238c8484779f491d1ae65aae2a68160933e4aa4d77b057a6

Observation 5636439d-25c0-4085-adf7-25fe5544a012 · outbound

This paper cites Scene compliant trajectory forecast with agent-centric spatio-temporal grids.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Scene compliant trajectory forecast with agent-centric spatio-temporal grids

Reference 98

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source=arxiv_source observed=2026-08-07T14:35:25.965906Z digest=sha256:ecfa895677807e67aefdb8a5b4a4b95dc007de2e79835a9f5f0890ee04552714

Observation 52f8e985-65bf-4511-8399-1045346ba955 · outbound

This paper cites Learning social etiquette: Human trajectory understanding in crowded scenes.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Learning social etiquette: Human trajectory understanding in crowded scenes

Reference 99

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source=arxiv_source observed=2026-08-07T14:35:25.969862Z digest=sha256:6c3fe705b8c47c75d80b9fac0bbe22dc375f7f09e98539e135e4df2413dbe30e

Observation aaacc2d1-8f5c-4e64-8e9e-465f72a18dbe · outbound

This paper cites Parallel distributed processing, volume 1: Explorations in the microstructure of cognition: Foundations.

Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review Parallel distributed processing, volume 1: Explorations in the microstructure of cognition: Foundations

Reference 100

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source=arxiv_source observed=2026-08-07T14:35:25.973511Z digest=sha256:d41e39bd4a107146037a9e5342ebac1b7c92032440469570d9bf694a2fc66a64

Pith citing papers

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