VideoPure: Diffusion-based Adversarial Purification for Video Recognition | Paper Citation Record

Observation ce74e9e5-f2a1-4034-b3ed-e4c54069281a · outbound

This paper cites Deep residual learning for image recognition,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Deep residual learning for image recognition,

Reference 1

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Observation e92dbc40-34a6-47f9-89e4-82ebe7fe8221 · outbound

This paper cites Towards practical certifiable patch defense with vision transformer,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Towards practical certifiable patch defense with vision transformer,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.669426Z

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Observation ad3565e6-3f26-4ca4-812e-354f2eec6c19 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Towards deep learning models resistant to adversarial attacks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.653254Z

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Observation 02b75289-9c15-4f44-81ba-311dcdb6192b · outbound

This paper cites Cross-shaped adversarial patch attack,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Cross-shaped adversarial patch attack,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.637106Z

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Observation 9497e1c2-7da0-4476-9834-bf99c57dff8b · outbound

This paper cites Adversarial attacks on video object segmentation with hard region discovery,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Adversarial attacks on video object segmentation with hard region discovery,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.620066Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f0c7a96-9392-4298-ba4a-eb96fd676cc0 · outbound

This paper cites Diffusion patch attack with spatial-temporal cross-evolution for video recognition,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Diffusion patch attack with spatial-temporal cross-evolution for video recognition,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.603541Z

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Observation 49e0b7d9-6488-4fcb-8679-2abf6ec3e5ac · outbound

This paper cites Bullet-screen-emoji attack with temporal difference noise for video action recognition,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Bullet-screen-emoji attack with temporal difference noise for video action recognition,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.586453Z

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Observation 8fcbc192-7b04-4a68-8beb-57b913d8517a · outbound

This paper cites Only once attack: Fooling the tracker with adversarial template,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Only once attack: Fooling the tracker with adversarial template,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.572050Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6c0e77df-854e-4956-aaf7-e3404bb8fd2f · outbound

This paper cites A simple and strong baseline for universal targeted attacks on siamese visual tracking,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition A simple and strong baseline for universal targeted attacks on siamese visual tracking,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.556944Z

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Observation 91544af2-f545-49ea-a4a7-452e6308deef · outbound

This paper cites Sparse adversarial perturbations for videos,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Sparse adversarial perturbations for videos,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.539961Z

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Observation f5676331-6795-4ed4-bd1b-a4906b0c525c · outbound

This paper cites The apolloscape dataset for autonomous driving,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition The apolloscape dataset for autonomous driving,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.522493Z

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Observation 133fc542-7941-48ab-9e9d-8e6a566389e4 · outbound

This paper cites A system for video surveillance and monitoring,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition A system for video surveillance and monitoring,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.505750Z

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 eb968ab7-43be-4ce5-a00b-8ccd74f19c67 · outbound

This paper cites Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples

Reference 13

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Observation 5d9a704f-a082-4713-88e7-ca82318b078e · outbound

This paper cites Theoretically principled trade-off between robustness and accuracy,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Theoretically principled trade-off between robustness and accuracy,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.489613Z

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Observation 830f13f9-bfd9-4db8-93cf-a71005cdc3c4 · outbound

This paper cites Improving robustness using generated data,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Improving robustness using generated data,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.475614Z

Source-reported events for the cited work

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Observation b20b4910-9da7-400f-9a59-f7aa56c4a8cd · outbound

This paper cites Adversarial machine learning at scale,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Adversarial machine learning at scale,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.461034Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b5100662-bed8-4544-924d-54470ded858d · outbound

This paper cites Defending against multiple and unforeseen adversarial videos,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Defending against multiple and unforeseen adversarial videos,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.446294Z

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Observation 2b8edc4b-b9c8-454e-9496-137fff938037 · outbound

This paper cites Analysis and extensions of adversarial training for video classification,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Analysis and extensions of adversarial training for video classification,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.429767Z

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 488c8c5b-2a2d-4fc6-befa-8f876e16e857 · outbound

This paper cites Defense-gan: Protecting classifiers against adversarial attacks using generative models,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Defense-gan: Protecting classifiers against adversarial attacks using generative models,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.413487Z

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Observation 7a07c090-283a-4e95-8faf-3da2cfa24340 · outbound

This paper cites Pixelde- fend: Leveraging generative models to understand and defend against adversarial examples,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Pixelde- fend: Leveraging generative models to understand and defend against adversarial examples,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.395525Z

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Observation 0fe90af3-bc98-49b5-b5fb-6cc7c79f7ff3 · outbound

This paper cites Defending video recognition model against adversarial perturbations via defense patterns,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Defending video recognition model against adversarial perturbations via defense patterns,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.379586Z

Source-reported events for the cited work

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Observation 0d72511e-38a0-41af-a0e1-0d96cd06c6cc · outbound

This paper cites Shield: Fast, practical defense and vaccination for deep learning using jpeg compression,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Shield: Fast, practical defense and vaccination for deep learning using jpeg compression,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.365738Z

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 2e4d48f9-c39f-4d60-8ac3-59b2c6a001f7 · outbound

This paper cites Defense for adversarial videos by self-adaptive jpeg compression and optical texture,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Defense for adversarial videos by self-adaptive jpeg compression and optical texture,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.350476Z

Source-reported events for the cited work

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Observation 89633f17-8433-4423-a41e-825893951d1d · outbound

This paper cites Temporal shuffling for defending deep action recognition models against adver- sarial attacks,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Temporal shuffling for defending deep action recognition models against adver- sarial attacks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.333445Z

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Observation f9060b8d-bd6b-4611-bd21-00c290314358 · outbound

This paper cites Diffusion models for adversarial purification,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Diffusion models for adversarial purification,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.314454Z

Source-reported events for the cited work

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Observation c7d0149b-7ce5-40ae-99df-d0dba432683a · outbound

This paper cites Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.295305Z

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Observation 37876f57-f152-4c3b-ac96-145716e92f54 · outbound

This paper cites Synthesizing robust adversarial examples,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Synthesizing robust adversarial examples,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.277100Z

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Observation 1f331525-e024-4651-8342-f81ad2e64319 · outbound

This paper cites Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.258556Z

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Observation 578b60d3-52e2-4774-9de7-25b2820b3bf6 · outbound

This paper cites Threat Model-Agnostic Adversarial Defense using Diffusion Models.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Threat Model-Agnostic Adversarial Defense using Diffusion Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.459111Z

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Observation 3bfe0234-0321-40ff-b2ca-0c8d819a56b8 · outbound

This paper cites Guided Diffusion Model for Adversarial Purification from Random Noise.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Guided Diffusion Model for Adversarial Purification from Random Noise

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.463696Z

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Observation 98d7040a-20fe-4181-a01a-afb4509652d0 · outbound

This paper cites Guided Diffusion Model for Adversarial Purification.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Guided Diffusion Model for Adversarial Purification

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.468719Z

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Observation 4c3eede9-0cee-447b-83d6-3bc58ace29d0 · outbound

This paper cites Enhancing adversarial robustness via score-based optimization,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Enhancing adversarial robustness via score-based optimization,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.241788Z

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 83f75e84-2df0-4406-8c81-e17f93a8fde3 · outbound

This paper cites Denoising diffusion probabilistic models,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Denoising diffusion probabilistic models,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.222890Z

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 a3151141-35fe-4e00-b640-99f8254924d9 · outbound

This paper cites ModelScope Text-to-Video Technical Report.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition ModelScope Text-to-Video Technical Report

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.482864Z

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Observation 60c4372d-858e-465d-b9ac-c218c9bed738 · outbound

This paper cites Denoising diffusion implicit models,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Denoising diffusion implicit models,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.206012Z

Source-reported events for the cited work

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Observation 95532c82-d9c2-4d24-b144-dc2e80482ff5 · outbound

This paper cites Intriguing properties of neural networks,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Intriguing properties of neural networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.188661Z

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Observation db155556-5feb-4238-809e-a250f2cd945f · outbound

This paper cites Boosting the transferability of video adversarial examples via temporal translation,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Boosting the transferability of video adversarial examples via temporal translation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.171398Z

Source-reported events for the cited work

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Observation d0ad1e5c-bc92-45b0-9b8a-577d00719179 · outbound

This paper cites Global-local characteristic excited cross-modal attacks from images to videos,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Global-local characteristic excited cross-modal attacks from images to videos,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.154418Z

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 ab761e5e-a164-4f71-b869-7c0cc7b55149 · outbound

This paper cites Cross-modal transferable adversarial attacks from images to videos,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Cross-modal transferable adversarial attacks from images to videos,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.134388Z

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 f95ea63a-935e-413c-a7f1-89a375810665 · outbound

This paper cites Black-box adversarial attacks on video recognition models,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Black-box adversarial attacks on video recognition models,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.116133Z

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 1b83e8db-c612-4f76-b4d6-3702753380ce · outbound

This paper cites Motion-excited sampler: Video adversarial attack with sparked prior,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Motion-excited sampler: Video adversarial attack with sparked prior,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.098925Z

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 812631fd-21ee-4cb3-8988-ec8a5b2a9c60 · outbound

This paper cites Efficient decision-based black-box patch attacks on video recognition,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Efficient decision-based black-box patch attacks on video recognition,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.071532Z

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 09b9773d-46a5-4c5e-999d-faaba698a456 · outbound

This paper cites Towards decision-based sparse attacks on video recognition,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Towards decision-based sparse attacks on video recognition,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.056144Z

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 86f26413-c8ea-4ccb-a275-5f118b86e20e · outbound

This paper cites Adversarial examples in the physical world,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Adversarial examples in the physical world,

Reference 44

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Observation 8ac818fc-f7ef-4a05-b5d2-2cee7034d8bc · outbound

This paper cites Adam: A Method for Stochastic Optimization.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Adam: A Method for Stochastic Optimization

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.531914Z

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Observation a2cafcf9-308e-4281-9539-f1f6b0d9a1a3 · outbound

This paper cites Just one moment: Structural vulnerability of deep action recognition against one frame attack,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Just one moment: Structural vulnerability of deep action recognition against one frame attack,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.030968Z

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 79179315-2d22-49b0-a65e-bf9949b6b640 · outbound

This paper cites Over-the-air adversarial flickering attacks against video recognition networks,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Over-the-air adversarial flickering attacks against video recognition networks,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.015521Z

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 67e50031-3515-45e6-a9e7-7bbbf327ee20 · outbound

This paper cites Diffattack: Evasion attacks against diffusion-based adversarial purification,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Diffattack: Evasion attacks against diffusion-based adversarial purification,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:58.000207Z

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 37c71e83-9c3f-4caa-85c3-3dcb4bb3b37e · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Explaining and Harnessing Adversarial Examples

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.550419Z

Source-reported events for the cited work

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Observation b3ff5745-6739-4af7-970b-014bd0917e3a · outbound

This paper cites Image super- resolution as a defense against adversarial attacks,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Image super- resolution as a defense against adversarial attacks,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.985129Z

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 bca7f215-d617-4df5-b449-186893f4c617 · outbound

This paper cites Taming transformers for high- resolution image synthesis,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Taming transformers for high- resolution image synthesis,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.970100Z

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 da685d1a-d509-4a33-9dd1-88fec0b708fa · outbound

This paper cites Null- text inversion for editing real images using guided diffusion models,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Null- text inversion for editing real images using guided diffusion models,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.955058Z

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 fc398202-6ca9-4b7e-88ce-7f37fe850eff · outbound

This paper cites Content-based unrestricted adversarial attack,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Content-based unrestricted adversarial attack,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.938848Z

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 bed7f4d2-731e-496e-822c-70122ea83b3c · outbound

This paper cites Diffusion Model-Based Image Editing: A Survey.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Diffusion Model-Based Image Editing: A Survey

Reference 54

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Observation ce323eeb-4c3f-4eb0-ac86-743b53891540 · outbound

This paper cites Text2video-zero: Text-to-image diffusion models are zero-shot video generators,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Text2video-zero: Text-to-image diffusion models are zero-shot video generators,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.924278Z

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 b02063a6-45da-43ad-b06e-3e6b5154587c · outbound

This paper cites Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Motion-Guided Latent Diffusion for Temporally Consistent Real-world Video Super-resolution

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.580422Z

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Observation 4843206b-ff90-4d7e-b130-353c9abe9257 · outbound

This paper cites UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.585048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfd6c725-14a9-4c57-ba15-4243fccb68c7 · outbound

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

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Quo vadis, action recognition? a new model and the kinetics dataset,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.908948Z

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 4d4a0b40-a8a0-4b21-b848-4f4035e3ad0c · outbound

This paper cites Non-local neural net- works,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Non-local neural net- works,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.893091Z

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 bb5cfc41-af0d-4fda-9d2a-180ad669201a · outbound

This paper cites Slowfast networks for video recognition,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Slowfast networks for video recognition,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.878183Z

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 fd8e2888-cca2-438e-85f7-a07cbc9fb49c · outbound

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

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Raft: Recurrent all-pairs field transforms for optical flow,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.606320Z

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Unavailable: canonical work link unavailable.

Observation 8f8830a6-f160-4fc2-9c37-6d4d37920a81 · outbound

This paper cites Boosting Adversarial Attacks with Momentum.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Boosting Adversarial Attacks with Momentum

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T14:48:57.610259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad82d70f-36ea-404b-8fc5-15119aa451c3 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition High- resolution image synthesis with latent diffusion models,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.852970Z

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 a3739b80-1aad-4e3c-b9ac-91410fbe8e90 · outbound

This paper cites Diffusion models beat gans on image synthesis,.

VideoPure: Diffusion-based Adversarial Purification for Video Recognition Diffusion models beat gans on image synthesis,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T14:48:57.836319Z

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.

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