Paper Citation Record · LEDGER

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

As of 7 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 8 inbound Pith citation observations for arXiv:2506.05372.

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

pith.paper-citation-record.v1
2506.05372 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:00:35.073145Z

measured 76 of 76 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:44:19.523313Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T11:44:38.866606Z

Reference resolution

68 of 68 outbound references displayed

verified exact11
verified fuzzy42
unresolved15
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 08dda51c-4a9c-46cc-af56-765d4b7005c9 · outbound

This paper cites Nefeli: A deep-learning detection and tracking pipeline for enhancing autonomy in advanced air mobility.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Nefeli: A deep-learning detection and tracking pipeline for enhancing autonomy in advanced air mobility

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:46.103876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df8ef92c-9d7b-45e5-8330-52f1bb382f51 · outbound

This paper cites A large imaging database and novel deep neural ar- chitecture for covid-19 diagnosis.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios A large imaging database and novel deep neural ar- chitecture for covid-19 diagnosis

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:45.786966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3a9059a6-9306-45b9-8b44-e6de05a75899 · outbound

This paper cites Data-driven covid-19 detection through medical imaging.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Data-driven covid-19 detection through medical imaging

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:45.371123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6412b46a-6872-4924-af19-275ac1fa454c · outbound

This paper cites Common Corruptions for Enhancing and Evaluating Robustness in Air-to-Air Visual Object Detection.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Common Corruptions for Enhancing and Evaluating Robustness in Air-to-Air Visual Object Detection

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:37.113441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 25d492e0-5224-46da-9b0c-4064721a858e · outbound

This paper cites Common corruptions for evaluating and enhancing robustness in air-to-air visual object detection.IEEE Robotics and Automation Letters, 2024.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Common corruptions for evaluating and enhancing robustness in air-to-air visual object detection.IEEE Robotics and Automation Letters, 2024

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:45.078394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 24dd7668-ec71-41da-be2f-f79dc22e1f06 · outbound

This paper cites Uncertainty- guided contrastive learning for single source domain gener- alisation.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Uncertainty- guided contrastive learning for single source domain gener- alisation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:44.819031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bcb22d54-1169-4c3f-98b9-06fa63360b40 · outbound

This paper cites Efficient human violence recognition for surveillance in real time.Sensors, 24(2), 2024.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Efficient human violence recognition for surveillance in real time.Sensors, 24(2), 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:44.573321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation abe6609b-58bc-4e6d-a8e0-6fe27f04c419 · outbound

This paper cites Violence detection in video using computer vision techniques.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Violence detection in video using computer vision techniques

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:44.327281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5e6cc9d2-8dc0-4915-a0e8-e15c25966bd6 · outbound

This paper cites Cue-net: Violence detection video analytics with spatial cropping, enhanced uniformerv2 and modified efficient additive attention.arXiv e-prints, pages arXiv–2404, 2024.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Cue-net: Violence detection video analytics with spatial cropping, enhanced uniformerv2 and modified efficient additive attention.arXiv e-prints, pages arXiv–2404, 2024

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:44.039401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 701cee7a-d572-4816-9da4-02e8af01d7e2 · outbound

This paper cites Rwf-2000: an open large scale video database for violence detection.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Rwf-2000: an open large scale video database for violence detection

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:43.783719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d072cae-e845-478f-bfa9-21d3cb482b3f · outbound

This paper cites COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI System.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios COVID-19 Computer-aided Diagnosis through AI-assisted CT Imaging Analysis: Deploying a Medical AI System

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:36.941399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0d3773a3-809c-4bf1-afdb-9cfcc6e65acb · outbound

This paper cites Violent flows: Real-time detection of violent crowd behavior.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Violent flows: Real-time detection of violent crowd behavior

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:43.521998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5104c90b-b1c7-49fe-8b3c-c2ee68bef4e0 · outbound

This paper cites Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Rethinking Affect Analysis: A Protocol for Ensuring Fairness and Consistency

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:36.804065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fb62c325-de63-4bb6-ad31-4af4db6c04ce · outbound

This paper cites Bridging the Gap: Protocol Towards Fair and Consistent Affect Analysis.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Bridging the Gap: Protocol Towards Fair and Consistent Affect Analysis

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:36.703523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ed82716-f2d8-4008-9f90-6ff4720bd269 · outbound

This paper cites Ensuring UAV Safety: A Vision-only and Real-time Framework for Collision Avoidance Through Object Detection, Tracking, and Distance Estimation.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Ensuring UAV Safety: A Vision-only and Real-time Framework for Collision Avoidance Through Object Detection, Tracking, and Distance Estimation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.766727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1154faa5-b275-4a3d-8b2f-0ec3f9de71d7 · outbound

This paper cites ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Multi-Task Learning Challenges

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:36.565826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9df1b55-5791-4dff-91ef-11f0e843e12f · outbound

This paper cites Multi-label compound expression recog- nition: C-expr database & network.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Multi-label compound expression recog- nition: C-expr database & network

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:43.253893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9181f463-f97a-45b2-b0ce-be26180936c3 · outbound

This paper cites Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Aff-Wild2: Extending the Aff-Wild Database for Affect Recognition

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:29.998509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3d79ef2-30ba-41c4-aa59-38e31058e744 · outbound

This paper cites A Multi-Task Learning & Generation Framework: Valence-Arousal, Action Units & Primary Expressions.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios A Multi-Task Learning & Generation Framework: Valence-Arousal, Action Units & Primary Expressions

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:36.417101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a52fa728-7d43-46b9-924c-060c80cf6e90 · outbound

This paper cites A Multi-component CNN-RNN Approach for Dimensional Emotion Recognition in-the-wild.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios A Multi-component CNN-RNN Approach for Dimensional Emotion Recognition in-the-wild

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:36.226106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 87210d53-44bf-482b-9447-3e444108cd13 · outbound

This paper cites Training deep neu- ral networks with different datasets in-the-wild: The emotion recognition paradigm.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Training deep neu- ral networks with different datasets in-the-wild: The emotion recognition paradigm

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:42.914567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1cbfcacd-f8eb-4a9e-9e59-8d19547bf410 · outbound

This paper cites Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.407123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dbed7cc-edef-48b4-b166-170fbbcde435 · outbound

This paper cites Va-stargan: Con- tinuous affect generation.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Va-stargan: Con- tinuous affect generation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:42.626512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fc824a59-39c1-4c76-84da-a1bda2a1138f · outbound

This paper cites Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.590253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48119709-b5ea-4be6-b7a7-7b679b373a03 · outbound

This paper cites Analysing affec- tive behavior in the second abaw2 competition.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Analysing affec- tive behavior in the second abaw2 competition

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:42.537361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a58a2a5f-3db6-4698-8b2c-666a0e578ad2 · outbound

This paper cites Exploiting multi-cnn features in cnn-rnn based dimensional emotion recognition on the omg in-the-wild dataset.IEEE Transac- tions on Affective Computing, 2020.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Exploiting multi-cnn features in cnn-rnn based dimensional emotion recognition on the omg in-the-wild dataset.IEEE Transac- tions on Affective Computing, 2020

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:42.419306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f94bd8ae-52ee-4c17-b1bf-33ea668b6257 · outbound

This paper cites Analysing affective behavior in the first abaw 2020 competition.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Analysing affective behavior in the first abaw 2020 competition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:42.243588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 51a0e07f-3773-4019-b6a7-7828e61aab4d · outbound

This paper cites Advancements in affective and behavior analysis: The 8th abaw workshop and competition.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Advancements in affective and behavior analysis: The 8th abaw workshop and competition

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:30.864529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f74e7d91-c540-4990-ba7f-41f2836f8af8 · outbound

This paper cites Inter- weaving deep learning and semantic techniques for emotion analysis in human-machine interaction.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Inter- weaving deep learning and semantic techniques for emotion analysis in human-machine interaction

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:42.001015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a8905e28-fac6-4aa1-b839-e2e7c580e983 · outbound

This paper cites On line emotion detection using retrainable deep neural networks.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios On line emotion detection using retrainable deep neural networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:41.824279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4827324f-c3b5-4346-8ee4-d356cf0ef4e9 · outbound

This paper cites Recognition of affect in the wild using deep neural networks.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Recognition of affect in the wild using deep neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:41.605061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 785cc5cc-5b9d-491b-8071-64819780a51c · outbound

This paper cites Adap- tation and contextualization of deep neural network models.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Adap- tation and contextualization of deep neural network models

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:41.367833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 69953360-3019-46b9-90d9-355101542c07 · outbound

This paper cites Photorealistic facial synthesis in the dimensional affect space.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Photorealistic facial synthesis in the dimensional affect space

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:41.261298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f6eedaeb-2487-4f84-aab3-584fc4448f82 · outbound

This paper cites Deep neural archi- tectures for prediction in healthcare.Complex & Intelligent Systems, 4(2):119–131, 2018.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Deep neural archi- tectures for prediction in healthcare.Complex & Intelligent Systems, 4(2):119–131, 2018

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:41.068919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bfcbcc7e-aabf-420e-a1d9-8163ac6b59e0 · outbound

This paper cites Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:31.734568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 818d26cb-490a-4cda-b52a-2867857a8e76 · outbound

This paper cites Deep affect prediction in-the-wild: Aff-wild database and challenge, deep architec- tures, and beyond.International Journal of Computer Vision, 127(6):907–929, 2019.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Deep affect prediction in-the-wild: Aff-wild database and challenge, deep architec- tures, and beyond.International Journal of Computer Vision, 127(6):907–929, 2019

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:40.955338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 041c0dd2-6dac-4bac-9004-57c2a1a886c4 · outbound

This paper cites Deep Transparent Prediction through Latent Representation Analysis.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Deep Transparent Prediction through Latent Representation Analysis

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:31.923105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db40acbf-9f18-4d59-aa5d-50d81d9135a0 · outbound

This paper cites Deep neural network augmentation: Generating faces for affect analysis.Interna- tional Journal of Computer Vision, pages 1–30, 2020.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Deep neural network augmentation: Generating faces for affect analysis.Interna- tional Journal of Computer Vision, pages 1–30, 2020

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:40.841892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 76c5d56c-0650-4c81-9e26-90c874557c02 · outbound

This paper cites Transpar- ent adaptation in deep medical image diagnosis.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Transpar- ent adaptation in deep medical image diagnosis

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:40.734318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67e7cd5a-ef24-4100-bf21-9044b9c7a32e · outbound

This paper cites Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:32.281001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55e73bd-c230-4aaf-8935-3c646950ef77 · outbound

This paper cites Ai-enabled analysis of 3-d ct scans for diagnosis of covid-19 & its severity.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Ai-enabled analysis of 3-d ct scans for diagnosis of covid-19 & its severity

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:40.602585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation efd7304f-0917-4dd0-9590-fb30e1a6448b · outbound

This paper cites A deep neural architecture for harmonizing 3-d input data analysis and decision making in medical imaging.Neuro- computing, 542:126244, 2023.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios A deep neural architecture for harmonizing 3-d input data analysis and decision making in medical imaging.Neuro- computing, 542:126244, 2023

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:40.502469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation deffd670-2195-412d-8aab-abef4ca33363 · outbound

This paper cites Ai-mia: Covid-19 detection and severity analysis through medical imaging.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Ai-mia: Covid-19 detection and severity analysis through medical imaging

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:40.364915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ae52388d-2bc9-4e3f-9527-51bc994aa45a · outbound

This paper cites MMA-MRNNet: Harnessing Multiple Models of Affect and Dynamic Masked RNN for Precise Facial Expression Intensity Estimation.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios MMA-MRNNet: Harnessing Multiple Models of Affect and Dynamic Masked RNN for Precise Facial Expression Intensity Estimation

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:35.987740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 25bee610-a385-453a-a38a-261a6811fe1b · outbound

This paper cites Abaw: Valence-arousal esti- mation, expression recognition, action unit detection & emo- tional reaction intensity estimation challenges.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Abaw: Valence-arousal esti- mation, expression recognition, action unit detection & emo- tional reaction intensity estimation challenges

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:40.098784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation df72a080-2458-4a8c-b08a-32e9a81625ae · outbound

This paper cites Btdnet: A multi-modal approach for brain tumor radiogenomic classification.Applied Sciences, 13(21):11984, 2023.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Btdnet: A multi-modal approach for brain tumor radiogenomic classification.Applied Sciences, 13(21):11984, 2023

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:39.859508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 75c08e44-4978-4dbd-8f51-5c339895140e · outbound

This paper cites Domain adaptation, Explainability & Fairness in AI for Medical Image Analysis: Diagnosis of COVID-19 based on 3-D Chest CT-scans.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Domain adaptation, Explainability & Fairness in AI for Medical Image Analysis: Diagnosis of COVID-19 based on 3-D Chest CT-scans

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:33.082776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 607a659c-ce70-43d1-8e10-e7c46391a26c · outbound

This paper cites SAM2CLIP2SAM: Vision Language Model for Segmentation of 3D CT Scans for Covid-19 Detection.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios SAM2CLIP2SAM: Vision Language Model for Segmentation of 3D CT Scans for Covid-19 Detection

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:33.183245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fcfa065-2d81-4505-bb20-8ee407fd1fdc · outbound

This paper cites Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Behaviour4All: in-the-wild Facial Behaviour Analysis Toolkit

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:33.304284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10c25ca1-fcd1-46de-94b4-f51cd53b8702 · outbound

This paper cites Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyond.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyond

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:35.730389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e784e6a0-42d6-4902-9f31-8e25b4b72941 · outbound

This paper cites The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios The 6th Affective Behavior Analysis in-the-wild (ABAW) Competition

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:35.509926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 64f9a534-0f4b-438d-8c74-6d92ab527fb4 · outbound

This paper cites 7th ABAW Competition: Multi-Task Learning and Compound Expression Recognition.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios 7th ABAW Competition: Multi-Task Learning and Compound Expression Recognition

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:33.604743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e953b569-4436-4e3f-b149-0a6fb443d0e0 · outbound

This paper cites Cowen, Ste- fanos Zafeiriou, Irene Kotsia, Eric Granger, Marco Peder- soli, Simon L.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Cowen, Ste- fanos Zafeiriou, Irene Kotsia, Eric Granger, Marco Peder- soli, Simon L

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:39.582585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 771cb178-9faa-4de2-9eb8-5c515aa70ac6 · outbound

This paper cites Can Machine Learning Assist in Diagnosis of Primary Immune Thrombocytopenia? A feasibility study.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Can Machine Learning Assist in Diagnosis of Primary Immune Thrombocytopenia? A feasibility study

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:00:35.285408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d9354a17-01c1-402a-b68a-21d64acdd6c2 · outbound

This paper cites A multi-stream cnn for deep violence detection in video sequences using handcrafted features.The Visual Computer, 38(6):2057–2072, 2022.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios A multi-stream cnn for deep violence detection in video sequences using handcrafted features.The Visual Computer, 38(6):2057–2072, 2022

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:39.384267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d6df1150-b7d2-4d5d-8f90-c15a35d0821d · outbound

This paper cites Movies fight detection dataset.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Movies fight detection dataset

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:39.153213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 762d98d6-8302-411d-afe9-4748662ec224 · outbound

This paper cites Mixaugment & mixup: Augmentation methods for facial expression recog- nition.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Mixaugment & mixup: Augmentation methods for facial expression recog- nition

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:33.952274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc8d908c-cb18-4585-8d32-cc100fe959c4 · outbound

This paper cites Medical image segmentation: A review of modern architec- tures.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Medical image segmentation: A review of modern architec- tures

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:38.951275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2bf6a1a3-d5cc-49f9-88fd-db8960a0cb76 · outbound

This paper cites Cue-net: violence detection video analytics with spatial cropping enhanced uniformerv2 and modified efficient additive attention.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Cue-net: violence detection video analytics with spatial cropping enhanced uniformerv2 and modified efficient additive attention

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:38.756371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7da2651f-14c0-4490-aa95-095720488dad · outbound

This paper cites Violence recog- nition from videos using deep learning techniques.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Violence recog- nition from videos using deep learning techniques

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:38.537926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ed253f52-db2f-49c5-926a-165958a417a0 · outbound

This paper cites Violence recog- nition from videos using deep learning techniques.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Violence recog- nition from videos using deep learning techniques

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:38.348201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a040b601-f22b-4d5b-a404-47a33f8ee7b3 · outbound

This paper cites Real-world anomaly detection in surveillance videos.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Real-world anomaly detection in surveillance videos

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:38.091033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9b31a714-cadd-4e48-9ad2-a4e38406436f · outbound

This paper cites Assessment of parkinson’s disease based on deep neural networks.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Assessment of parkinson’s disease based on deep neural networks

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:37.911787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 97449d7d-0400-4c3c-853b-9d41d0903dc0 · outbound

This paper cites an unresolved cited work.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:00:37.771886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4e38524-12b8-4ba6-8b3f-d0108be8d6fb · outbound

This paper cites Not only look, but also listen: Learning multimodal violence detection under weak supervision.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Not only look, but also listen: Learning multimodal violence detection under weak supervision

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T13:00:34.778892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87f5b54e-9cb0-45c3-bb69-f0976db6c98e · outbound

This paper cites Video violence rating: A large-scale public database and a multimodal rating model.IEEE Transactions on Multimedia, 26:8557–8568,.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Video violence rating: A large-scale public database and a multimodal rating model.IEEE Transactions on Multimedia, 26:8557–8568,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:37.616997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 04a8ce9b-e34f-4a7d-8967-4487d4af5ddb · outbound

This paper cites Berg, and Dimitris Samaras.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Berg, and Dimitris Samaras

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:37.476501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5045005d-f87d-4440-9972-008e0ac83e63 · outbound

This paper cites Aff-wild: Valence and arousal ‘in-the-wild’challenge.

DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios Aff-wild: Valence and arousal ‘in-the-wild’challenge

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:00:37.256986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation ddafcc4c-10e6-4836-ad3c-b488f9ed466a · inbound

TAGF: Time-aware Gated Fusion for Multimodal Valence-Arousal Estimation cites this paper.

TAGF: Time-aware Gated Fusion for Multimodal Valence-Arousal Estimation DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T20:44:19.523313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4119882-8400-43e3-9f5c-2714479a7099 · inbound

Team RAS in 9th ABAW Competition: Multimodal Compound Expression Recognition Approach cites this paper.

Team RAS in 9th ABAW Competition: Multimodal Compound Expression Recognition Approach DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T20:40:00.706801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ea1e798-be1b-4d9b-bb88-2c9041fe3de5 · inbound

Distance-aware Soft Prompt Guidance for Multimodal Valence-Arousal Estimation cites this paper.

Distance-aware Soft Prompt Guidance for Multimodal Valence-Arousal Estimation DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T18:22:01.392376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b11018d1-2fc8-4172-89fa-b3110672f690 · inbound

Distance-aware Soft Prompt Guidance for Multimodal Valence-Arousal Estimation cites this paper.

Distance-aware Soft Prompt Guidance for Multimodal Valence-Arousal Estimation DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T02:33:54.073096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34397db5-29b3-4916-9a45-bda6b44f7701 · inbound

AViS-Mamba: Adaptive Visual Steering of Audio State-Space Dynamics for Violence Detection cites this paper.

AViS-Mamba: Adaptive Visual Steering of Audio State-Space Dynamics for Violence Detection DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:13:16.637791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 82afc6d2-c73d-4799-8a4a-3a03fe63d996 · inbound

From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition cites this paper.

From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T11:44:38.868132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7be7aafb-8799-4289-9767-7390565ef0d8 · inbound

Child-Oriented AIGC Video Risk Reviewing: A Benchmark and Knowledge-Supported Iterative Reasoning Framework cites this paper.

Child-Oriented AIGC Video Risk Reviewing: A Benchmark and Knowledge-Supported Iterative Reasoning Framework DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T13:13:54.391510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c85052ad-3a78-48d0-9fdd-0e2be3abff50 · inbound

EgoSafe: A First-Person Mobile-Captured Benchmark for Visual Safety Understanding cites this paper.

EgoSafe: A First-Person Mobile-Captured Benchmark for Visual Safety Understanding DVD: A Comprehensive Dataset for Advancing Violence Detection in Real-World Scenarios

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T14:08:26.709687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.