Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:14:12.492084Z
Paper Citation Record · LEDGER
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions
As of 18 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2505.07611.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
69 of 69 outbound references displayed
- verified exact1
- verified fuzzy61
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 35078c05-3b69-400f-9950-d4ca7dc3d20c · outbound
This paper cites (2021, December 3).
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions (2021, December 3)
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.379090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9cad3fba-2112-41d2-9dbc-93013ff08cbd · outbound
This paper cites Road traffic injuries,.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Road traffic injuries,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.367384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ed2d7ce4-9291-4103-91a0-3328d9aafb3b · outbound
This paper cites Improving the transferability of the crash prediction model using the TrAdaBoost.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Improving the transferability of the crash prediction model using the TrAdaBoost
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.353531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d891a6f9-daa1-4991-9d06-7d3d51d501fc · outbound
This paper cites A., & Alozi, A.
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.341614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 137c6d4d-ff57-4439-965e-27c83a5bd381 · outbound
This paper cites F., & Capretz, M.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions F., & Capretz, M
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.330606Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation adb27bbb-ff95-47da-9fcb-58104b9dffdc · outbound
This paper cites F., Alam, M.
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.320855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4f3b09b9-aa4f-45f4-8b25-108f1799c343 · outbound
This paper cites Vision-based traffic accident detection and anticipation: A survey.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Vision-based traffic accident detection and anticipation: A survey
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.308436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 04be351b-e5cd-4421-8a22-6130113705c0 · outbound
This paper cites an unresolved cited work.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T22:14:13.297545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7e0e76a2-e3d9-4d1a-905d-b43e7d761816 · outbound
This paper cites Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:14:12.243026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dbc9580a-e97b-41e9-ad77-aad87edb648f · outbound
This paper cites Vision-Based Accident Anticipation and Detection Using Deep Learning.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Vision-Based Accident Anticipation and Detection Using Deep Learning
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.286835Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 39fb0000-27c5-4d3a-8e79-b76d5a74110c · outbound
This paper cites W., & Chung, K.
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.274661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7d1b0ccd-9735-4c54-818b-4813596518f3 · outbound
This paper cites V., Yu, S.
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.263855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e62fc56e-30e5-45c0-a046-fd08954a9da1 · outbound
This paper cites Predicting real-time traffic conflicts using deep learning.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Predicting real-time traffic conflicts using deep learning
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.250995Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2a7477f8-aaa2-4142-a04f-5286ba9aa82e · outbound
This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Are we ready for autonomous driving? the kitti vision benchmark suite
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.238413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d9b5c0fd-976d-4234-a846-0499c8e9f9d4 · outbound
This paper cites Uncertainty-based traffic accident anticipation with spatio-temporal relational learning.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Uncertainty-based traffic accident anticipation with spatio-temporal relational learning
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.226624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bba8d20d-5a0b-48c2-a12a-1430886b7680 · outbound
This paper cites P., Lamare, J.
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.213115Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2a8ae7c2-21d4-4418-b172-03ba1e85da56 · outbound
This paper cites H., Chen, Y.
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.198413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ddef7d9a-1627-4dd0-a416-7dbbe9dd146f · outbound
This paper cites Anticipating traffic accidents with adaptive loss and large- scale incident db.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Anticipating traffic accidents with adaptive loss and large- scale incident db
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.184534Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fc33fd39-ad8b-4fcc-99c9-d5f30fd50563 · outbound
This paper cites Joint pedestrian detection and risk-level prediction with motion-representation-by-detection.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Joint pedestrian detection and risk-level prediction with motion-representation-by-detection
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.171678Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2bc3a4fc-5d36-4604-a7a6-89c895656b11 · outbound
This paper cites GSC: A graph and spatio-temporal continuity based framework for accident anticipation.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions GSC: A graph and spatio-temporal continuity based framework for accident anticipation
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.159728Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 40c8dcac-b918-4447-8f72-f80852974c9a · outbound
This paper cites H., & Li, J.
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.146954Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d260ba6d-2ee5-494b-91c2-9045da481007 · outbound
This paper cites Sutd-trafficqa: A question answering benchmark and an efficient network for video reasoning over traffic events.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Sutd-trafficqa: A question answering benchmark and an efficient network for video reasoning over traffic events
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.135625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 57164a27-eb6e-4a96-a081-e36b969dc8da · outbound
This paper cites DADA: Driver attention prediction in driving accident scenarios.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions DADA: Driver attention prediction in driving accident scenarios
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.123919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 77372487-dbb3-4b53-ab4c-d218b50533f8 · outbound
This paper cites Crash to not crash: Learn to identify dangerous vehicles using a simulator.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Crash to not crash: Learn to identify dangerous vehicles using a simulator
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.112439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3df9804c-ba50-411f-abdb-fc790fc5cb40 · outbound
This paper cites an unresolved cited work.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Unresolved cited work
Reference 25
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T22:14:13.099522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 025f660b-3661-4dbc-a658-ce0d1fac4491 · outbound
This paper cites Deep learning.
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.088424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7f72e37a-c632-4d10-9865-ec581ab82016 · outbound
This paper cites When, Where, and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions When, Where, and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:14:12.315029Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 89382bb4-278e-40c0-9876-3f6b7bf8f2a7 · outbound
This paper cites Gradient-based learning applied to document recognition.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Gradient-based learning applied to document recognition
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.078161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a411c6c2-b919-464b-a952-1370a35bb51f · outbound
This paper cites Vision transformer for detecting critical situations and extracting functional scenario for automated vehicle safety assessment.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Vision transformer for detecting critical situations and extracting functional scenario for automated vehicle safety assessment
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.067738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1a0415c7-8035-437c-8344-eb9cbef26bd6 · outbound
This paper cites R., & Osman, O.
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.056415Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f7276b84-1853-4500-830e-006493948f15 · outbound
This paper cites Deep learning methods and applications.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Deep learning methods and applications
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.045117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 96acaf90-aec0-41cf-aae0-55b5f32cdefe · outbound
This paper cites Long Short-term Memory.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Long Short-term Memory
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.032920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 159aaaa6-1eae-495b-8ace-be0f48b7c980 · outbound
This paper cites an unresolved cited work.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Unresolved cited work
Reference 33
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T22:14:13.018920Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d933407a-6bf0-4d02-8fa9-cd867d2e4cb9 · outbound
This paper cites Cognitive Accident Prediction in Driving Scenes: A Multimodality Benchmark.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Cognitive Accident Prediction in Driving Scenes: A Multimodality Benchmark
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:14:12.343024Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 22bfa838-ae17-48b5-8a9a-9982d4406a00 · outbound
This paper cites & Bengio, Y.
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:13.007410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2a89db5d-80b3-4ac2-a3c8-9e1078a2ae6a · outbound
This paper cites Automated traffic incident detection with a smaller dataset based on generative adversarial networks.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Automated traffic incident detection with a smaller dataset based on generative adversarial networks
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.997000Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4b7ecaa0-dee0-43a7-874f-d257d54daf69 · outbound
This paper cites Real-time crash prediction on expressways using deep generative models.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Real-time crash prediction on expressways using deep generative models
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.986485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2c8b0bcc-61f2-4934-8c68-56f29c94621e · outbound
This paper cites Traffic accident data generation based on improved generative adversarial networks.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Traffic accident data generation based on improved generative adversarial networks
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.974888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3d424a7e-f401-40f4-817d-a8e9919bc832 · outbound
This paper cites COLLIDE-PRED: Prediction of On-Road Collision From Surveillance Videos.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions COLLIDE-PRED: Prediction of On-Road Collision From Surveillance Videos
Reference 39
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T22:14:12.544556Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 741308bc-f227-4bba-8e1b-2e0dbffe5476 · outbound
This paper cites Multi-modal fusion transformer for end-to-end autonomous driving.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Multi-modal fusion transformer for end-to-end autonomous driving
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.964618Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 86064e4c-3864-4936-bdf6-b6a61161cbae · outbound
This paper cites C., Hagenbuchner, M., & Monfardini, G.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions C., Hagenbuchner, M., & Monfardini, G
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.952492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0b40e53e-5f83-4e20-bfcb-a86d220a1690 · outbound
This paper cites Dynamic attention augmented graph network for video accident anticipation.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Dynamic attention augmented graph network for video accident anticipation
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.941835Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ab6ab6ea-1686-4d28-ba49-4127d2827bec · outbound
This paper cites Y., & Berg, A.
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.928379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 34ae1813-91a5-4941-8e21-2a3bace7e237 · outbound
This paper cites Modern data sources and techniques for analysis and forecast of road accidents: A review.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Modern data sources and techniques for analysis and forecast of road accidents: A review
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.917078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1742c6a1-bf26-4fd1-a03f-d7082df58cc7 · outbound
This paper cites I., Zaghdoud, R., Ahmed, M.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions I., Zaghdoud, R., Ahmed, M
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.906667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0463babb-37b6-41be-b860-51a3f32e3c39 · outbound
This paper cites S., & Zettsu, K.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions S., & Zettsu, K
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.896478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2050ebcd-180c-45ea-bd82-2a6314c6dc75 · outbound
This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Rich feature hierarchies for accurate object detection and semantic segmentation
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.885961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b1f06fdc-6dd3-420b-8ae1-adf1f67f0b16 · outbound
This paper cites A vehicle detection and tracking method for traffic video based on faster R- CNN.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions A vehicle detection and tracking method for traffic video based on faster R- CNN
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.874910Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e9f40e75-8ff9-4c51-accd-477bdc546c32 · outbound
This paper cites DRIVE: Deep reinforced accident anticipation with visual explanation.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions DRIVE: Deep reinforced accident anticipation with visual explanation
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.850922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e1af8dbf-b16a-4eaf-9e4f-2905c41295c3 · outbound
This paper cites DADA: Driver attention prediction in driving accident scenarios.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions DADA: Driver attention prediction in driving accident scenarios
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.837604Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f9e60204-3750-47dc-b237-f3d61694b98c · outbound
This paper cites M., Li, Y., Qin, R., & Yin, Z.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions M., Li, Y., Qin, R., & Yin, Z
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.862869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0a6e30d1-4a0e-4eef-88c4-a5acefe26f58 · outbound
This paper cites A Critical Review of Recurrent Neural Networks for Sequence Learning.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions A Critical Review of Recurrent Neural Networks for Sequence Learning
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:14:12.422009Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e167a9b1-11e2-4958-b5da-ce081b84dbbf · outbound
This paper cites Automatic Detection for Road Voids from GPR Images using Deep Learning Method.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Automatic Detection for Road Voids from GPR Images using Deep Learning Method
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.825030Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 337ddd79-1e2f-46e3-9492-15a2f7bc6bb9 · outbound
This paper cites C., Lee, C.
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.812198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 507c4970-738c-4b65-84af-e406fb0ac428 · outbound
This paper cites Predicting traffic accidents with event recorder data.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Predicting traffic accidents with event recorder data
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.800993Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6608e8c5-6995-4b23-9aec-06c5d394869c · outbound
This paper cites THAT-Net: Two-layer hidden state aggregation based two-stream network for traffic accident prediction.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions THAT-Net: Two-layer hidden state aggregation based two-stream network for traffic accident prediction
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.790288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 50a904e9-3a28-4017-af37-f10e1a60e6f4 · outbound
This paper cites GSNet: Learning spatial-temporal correlations from geographical and semantic aspects for traffic accident risk forecasting.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions GSNet: Learning spatial-temporal correlations from geographical and semantic aspects for traffic accident risk forecasting
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.774012Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 23433020-82d2-4093-a191-dcfe991dd21e · outbound
This paper cites Traffic accident prediction using vehicle tracking and trajectory analysis.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Traffic accident prediction using vehicle tracking and trajectory analysis
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.760968Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d0528adf-468a-4823-9274-0c5636ba7e6e · outbound
This paper cites Utilizing support vector machine in real-time crash risk evaluation.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Utilizing support vector machine in real-time crash risk evaluation
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.745180Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b2572d50-631f-494f-97bf-086ac47be7a9 · outbound
This paper cites A., & Tian, Z.
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.731119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a01074a5-6c55-4fd7-99b2-088e3b629b02 · outbound
This paper cites Dada-2000: Can driving accident be predicted by driver attentionƒ analyzed by a benchmark.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Dada-2000: Can driving accident be predicted by driver attentionƒ analyzed by a benchmark
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.719165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a6fabbec-8701-4bd1-9324-31a15c60cc99 · outbound
This paper cites Traffic Accident Prediction using Graph Neural Networks: New Datasets and the TRAVEL Model.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Traffic Accident Prediction using Graph Neural Networks: New Datasets and the TRAVEL Model
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.705129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b372271c-6d5a-4608-a6a6-d42b48208ece · outbound
This paper cites RiskOracle: A minute-level citywide traffic accident forecasting framework.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions RiskOracle: A minute-level citywide traffic accident forecasting framework
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.692579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 26f4ceb0-d1ad-4639-9c49-c915f5f024df · outbound
This paper cites A., Rehman, F.
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.679817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b7b21530-fa5f-4bb6-a70b-b7a5877817d2 · outbound
This paper cites An end-to-end online traffic-risk incident prediction in first-person dash camera videos.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions An end-to-end online traffic-risk incident prediction in first-person dash camera videos
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.665110Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8f3d4778-9cc9-4b7e-a9c3-e66dc0c169ae · outbound
This paper cites H., Chou, S.
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.650202Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 12212421-ee93-43f1-a4d7-ff54854989f5 · outbound
This paper cites NAVIBox: Real-Time Vehicle–Pedestrian Risk Prediction System in an Edge Vision Environment.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions NAVIBox: Real-Time Vehicle–Pedestrian Risk Prediction System in an Edge Vision Environment
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.636150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 81cbfc14-204c-4a4a-96c6-308e8891e533 · outbound
This paper cites L., Fang, J., & Xue, J.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions L., Fang, J., & Xue, J
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.620376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 34f92cf7-a2ee-4ba0-9a4d-86725089f13e · outbound
This paper cites Graph (Graph): A Nested Graph-Based Framework for Early Accident Anticipation.
Deep Learning Advances in Vision-Based Traffic Accident Anticipation: A Comprehensive Review of Methods, Datasets, and Future Directions Graph (Graph): A Nested Graph-Based Framework for Early Accident Anticipation
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:14:12.605485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
No inbound Pith citation observations are available.