Paper Citation Record · LEDGER

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection

As of 18 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2505.13123.

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

pith.paper-citation-record.v1
2505.13123 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:24:56.889476Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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verified fuzzy26
unresolved16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b95d5db5-3dd8-459a-84c9-9d908ec12779 · outbound

This paper cites Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.648065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23dc0409-d132-4b0a-a330-b2898e811c49 · outbound

This paper cites Prompt-enhanced multiple instance learning for weakly supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Prompt-enhanced multiple instance learning for weakly supervised video anomaly detection

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.586536Z

Source-reported events for the cited work

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Observation 95fdad44-fabb-4749-8a84-b0f4d9edaebb · outbound

This paper cites Tevad: Improved video anomaly de- tection with captions.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Tevad: Improved video anomaly de- tection with captions

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.660976Z

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Observation 7f83dc07-f600-4cf0-a7c1-fe2eb096d372 · outbound

This paper cites Mgfn: Magnitude- contrastive glance-and-focus network for weakly-supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Mgfn: Magnitude- contrastive glance-and-focus network for weakly-supervised video anomaly detection

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.557159Z

Source-reported events for the cited work

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Observation 9efd73f2-8bd3-410f-8e01-32a011d7ca07 · outbound

This paper cites Look around for anomalies: Weakly-supervised anomaly detection via context-motion relational learning.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Look around for anomalies: Weakly-supervised anomaly detection via context-motion relational learning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.539223Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 42800668-7253-46f6-9cf3-9662f9240a32 · outbound

This paper cites Learning an augmented rgb representation with cross-modal knowl- edge distillation for action detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Learning an augmented rgb representation with cross-modal knowl- edge distillation for action detection

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.522366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 64d08770-84c6-4403-9cce-ccb880f760cc · outbound

This paper cites Vpn: Learning video-pose embedding for activities of daily living, 2020.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Vpn: Learning video-pose embedding for activities of daily living, 2020

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.506467Z

Source-reported events for the cited work

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Observation e2492c97-e8e5-4eb4-85d8-df95798da993 · outbound

This paper cites Vpn++: Rethinking video-pose embeddings for understand- ing activities of daily living.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Vpn++: Rethinking video-pose embeddings for understand- ing activities of daily living

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.489605Z

Source-reported events for the cited work

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Observation 1452f70c-58e7-42cc-8b2e-38608524338c · outbound

This paper cites Imagebind: One embedding space to bind them all.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Imagebind: One embedding space to bind them all

Reference 9

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Source-reported events for the cited work

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Observation 7ce29d11-59a1-4dbc-913d-a90f32250bef · outbound

This paper cites Clip-tsa: Clip-assisted temporal self-attention for weakly-supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Clip-tsa: Clip-assisted temporal self-attention for weakly-supervised video anomaly detection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.461380Z

Source-reported events for the cited work

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Observation ff7b3e0d-c30d-463d-9751-d86189c2c057 · outbound

This paper cites The Kinetics Human Action Video Dataset.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection The Kinetics Human Action Video Dataset

Reference 11

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Source-reported events for the cited work

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Observation 69409e2d-c2b9-45fa-b135-b3ee0e75212f · outbound

This paper cites Segment any- thing.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Segment any- thing

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.717625Z

Source-reported events for the cited work

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Observation 68f95dab-52ef-4961-9b67-ca8bc2a953dc · outbound

This paper cites Scale-aware spatio-temporal relation learning for video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Scale-aware spatio-temporal relation learning for video anomaly detection

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.723104Z

Source-reported events for the cited work

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Observation f84d907f-048b-4570-a522-cc4c32e5db63 · outbound

This paper cites Self-training multi- sequence learning with transformer for weakly supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Self-training multi- sequence learning with transformer for weakly supervised video anomaly detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.423402Z

Source-reported events for the cited work

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Observation ca3fbca4-a234-4013-b681-b13c2a57cb37 · outbound

This paper cites Scaling (Down) CLIP: A Comprehensive Analysis of Data, Architecture, and Training Strategies.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Scaling (Down) CLIP: A Comprehensive Analysis of Data, Architecture, and Training Strategies

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:24:57.007406Z

Source-reported events for the cited work

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Observation 93eed785-4ea6-4f20-b6ca-0de2dd6cd244 · outbound

This paper cites Social mil: Interaction-aware for crowd anomaly de- tection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Social mil: Interaction-aware for crowd anomaly de- tection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.407157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7668f47a-152f-4946-8a46-8861bf148c0b · outbound

This paper cites Localizing anomalies from weakly-labeled videos.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Localizing anomalies from weakly-labeled videos

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.744849Z

Source-reported events for the cited work

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Observation 40606378-cffa-415d-844c-113d137359e2 · outbound

This paper cites Unbiased multiple instance learning for weakly supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Unbiased multiple instance learning for weakly supervised video anomaly detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.381201Z

Source-reported events for the cited work

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Observation ebee4e73-0dc9-4290-825a-ee4dfe9615c2 · outbound

This paper cites Weakly-supervised joint anomaly detection and classification.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Weakly-supervised joint anomaly detection and classification

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.365128Z

Source-reported events for the cited work

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Observation e78410e6-5420-4578-96d5-353d082d0d81 · outbound

This paper cites Dam: Dissimilarity attention module for weakly-supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Dam: Dissimilarity attention module for weakly-supervised video anomaly detection

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.349369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7f31b0e0-2c02-4b10-95e1-e4a2c77a3a41 · outbound

This paper cites Human- scene network: A novel baseline with self-rectifying loss for weakly supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Human- scene network: A novel baseline with self-rectifying loss for weakly supervised video anomaly detection

Reference 21

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Source-reported events for the cited work

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Observation 65ec70e5-b51e-4bdb-89a4-34accaec034d · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Representation Learning with Contrastive Predictive Coding

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.771501Z

Source-reported events for the cited work

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Observation f48e365e-0b0f-4543-9814-677fec1fe853 · outbound

This paper cites Dance with self-attention: A new look of conditional ran- dom fields on anomaly detection in videos.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Dance with self-attention: A new look of conditional ran- dom fields on anomaly detection in videos

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.319762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a742a6a7-24d6-4252-8446-0f15dba9e65e · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Learning transferable visual models from natural language supervi- sion

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.782065Z

Source-reported events for the cited work

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Observation 7c317c1c-19c2-46e3-bdd9-a92f477efa0d · outbound

This paper cites Fine-tuned clip models are efficient video learners.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Fine-tuned clip models are efficient video learners

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.292668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e2e3ba5b-954f-4ebf-aa30-bb04f6e01d07 · outbound

This paper cites Just add π! pose induced video transformers for understanding activities of daily liv- ing.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Just add π! pose induced video transformers for understanding activities of daily liv- ing

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.277141Z

Source-reported events for the cited work

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Observation 6804f9d8-6d43-4199-8573-8ceda99f2f69 · outbound

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

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Real-world anomaly detection in surveillance videos

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.261712Z

Source-reported events for the cited work

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Observation 86474913-626d-40cd-9b2d-2d4284e77608 · outbound

This paper cites Raft: Recurrent all-pairs field transforms for optical flow.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Raft: Recurrent all-pairs field transforms for optical flow

Reference 28

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Source-reported events for the cited work

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Observation 74758ab5-26c0-4739-be7f-e9e0baf81e6d · outbound

This paper cites Weakly-supervised video anomaly detection with robust temporal feature magni- tude learning.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Weakly-supervised video anomaly detection with robust temporal feature magni- tude learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.234239Z

Source-reported events for the cited work

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Observation 1bc1b032-66c1-4fa5-8dd9-0fdf34a24bd8 · outbound

This paper cites Weakly supervised video anomaly detection via center- guided discriminative learning.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Weakly supervised video anomaly detection via center- guided discriminative learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.217403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 49b9cb86-74ab-4069-aa88-2faf6ed6c841 · outbound

This paper cites Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.201038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 147ee4fd-5f06-423b-89cf-2d4b2a8a7acd · outbound

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

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Not only look, but also listen: Learning multimodal violence detection under weak supervision

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.184406Z

Source-reported events for the cited work

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Observation c628dcd7-3a88-42bb-adb3-7dd12b8bff55 · outbound

This paper cites Vadclip: Adapting vision-language models for weakly supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Vadclip: Adapting vision-language models for weakly supervised video anomaly detection

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.168381Z

Source-reported events for the cited work

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Observation 54c40331-a4c4-4ad8-bfc8-cfb92aebddf4 · outbound

This paper cites Depth Anything V2.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Depth Anything V2

Reference 34

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Source-reported events for the cited work

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Observation 51214634-1f10-422e-8818-f187adf2fb04 · outbound

This paper cites Text prompt with nor- mality guidance for weakly supervised video anomaly detec- tion.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Text prompt with nor- mality guidance for weakly supervised video anomaly detec- tion

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.152886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76f64d8f-92bd-4db2-880a-52a986c915ca · outbound

This paper cites Modality-aware contrastive instance learning with self-distillation for weakly-supervised audio-visual violence detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Modality-aware contrastive instance learning with self-distillation for weakly-supervised audio-visual violence detection

Reference 36

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Source-reported events for the cited work

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Observation 0f9f73d9-196b-4a22-9c99-d54eb9181e76 · outbound

This paper cites A self-reasoning framework for anomaly detection using video-level labels.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection A self-reasoning framework for anomaly detection using video-level labels

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.124437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5d2012f1-9070-4ee5-8369-67c395266c08 · outbound

This paper cites Exploiting completeness and uncertainty of pseudo labels for weakly supervised video anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Exploiting completeness and uncertainty of pseudo labels for weakly supervised video anomaly detection

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.863574Z

Source-reported events for the cited work

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Observation aca5a216-c972-486c-a39a-6bd99eb7cdcf · outbound

This paper cites Temporal con- volutional network with complementary inner bag loss for weakly supervised anomaly detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Temporal con- volutional network with complementary inner bag loss for weakly supervised anomaly detection

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.093197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7486cbcf-d03c-4524-a743-8d2354094cb0 · outbound

This paper cites Li, and Ge Li.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Li, and Ge Li

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.076132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1e9d7f87-abff-401c-aad5-74441c072566 · outbound

This paper cites Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.878401Z

Source-reported events for the cited work

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Observation aa25fad3-a07c-47f0-8b44-15d3934c9e7a · outbound

This paper cites Advancing video anomaly detection: A concise re- view and a new dataset.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Advancing video anomaly detection: A concise re- view and a new dataset

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:24:57.059072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b2d06a8f-dfd9-4911-9641-01fe7db2386a · outbound

This paper cites Motion-Aware Feature for Improved Video Anomaly Detection.

Just Dance with $\pi$! A Poly-modal Inductor for Weakly-supervised Video Anomaly Detection Motion-Aware Feature for Improved Video Anomaly Detection

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T20:24:56.889476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

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