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Paper Citation Record · LEDGER

AnyI2V: Animating Any Conditional Image with Motion Control

As of 7 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 1 inbound Pith citation observation for arXiv:2507.02857.

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

pith.paper-citation-record.v1
2507.02857 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:25:29.212390Z

measured 58 of 58 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T16:19:51.348169Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:28:38.518422Z

Reference resolution

57 of 57 outbound references displayed

  • verified exact3
  • verified fuzzy25
  • unresolved29
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1fed75c3-b20c-4f6b-96ac-78b1a717cd86 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

AnyI2V: Animating Any Conditional Image with Motion Control Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 1

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no resolver link, observed 2026-08-06T20:25:24.234995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:24.234995Z digest=sha256:0f49a14ddaaeffc25a4bff22689a8a7728aabe86bfc836f8862a7468d66b94a1

Observation 88234fc6-27ef-4f33-83cd-dc35b5f64f2a · outbound

This paper cites Align your latents: High-resolution video synthesis with latent diffusion models.

AnyI2V: Animating Any Conditional Image with Motion Control Align your latents: High-resolution video synthesis with latent diffusion models

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:34.460141Z

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.

source=pdf_text observed=2026-08-06T20:25:24.323877Z digest=sha256:a9062e5fcc481d0323380979370e794a9876f520284ee4d89cd4d16a442a8866

Observation efdf9c10-8737-47a9-a29a-4edda0d43b45 · outbound

This paper cites A unified 3d human motion synthesis model via conditional variational auto-encoder.

AnyI2V: Animating Any Conditional Image with Motion Control A unified 3d human motion synthesis model via conditional variational auto-encoder

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:34.328860Z

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.

source=pdf_text observed=2026-08-06T20:25:24.413431Z digest=sha256:1a3f70d8a4ba80fdb3b0b826647772e29ac98340a46eaa351487cd7c7ea7d7dc

Observation 47fb6f8e-8c13-427a-8c2c-c82e2e41c664 · outbound

This paper cites VideoCrafter1: Open Diffusion Models for High-Quality Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Reference 4

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no resolver link, observed 2026-08-06T20:25:24.503120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:24.503120Z digest=sha256:e8dc39fcf1aeca5d84f41ecd3c706bfb7be9c76a4ee8cb07d531c8f8a973c079

Observation 537051c3-c895-478e-8dab-e699d1e73474 · outbound

This paper cites Videocrafter2: Overcoming data limitations for high-quality video diffusion models.

AnyI2V: Animating Any Conditional Image with Motion Control Videocrafter2: Overcoming data limitations for high-quality video diffusion models

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:34.189521Z

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.

source=pdf_text observed=2026-08-06T20:25:24.594083Z digest=sha256:5202eff48e9d44c4c2d62ac63bbd28586ad04fa50f6dd7b1e60d446007033e56

Observation 78f7342e-fe75-436f-8721-6dfd29aad377 · outbound

This paper cites MeViS: A large-scale benchmark for video segmentation with motion expressions.

AnyI2V: Animating Any Conditional Image with Motion Control MeViS: A large-scale benchmark for video segmentation with motion expressions

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:33.997665Z

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.

source=pdf_text observed=2026-08-06T20:25:24.679423Z digest=sha256:61dab2e1a49879ed36ad71b3c11926b192d3f57be4695b1c16676873a4ddecab

Observation 8991ac9c-0e5e-49cd-86b0-9fe1b6ca30f8 · outbound

This paper cites AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning.

AnyI2V: Animating Any Conditional Image with Motion Control AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 7

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no resolver link, observed 2026-08-06T20:25:24.769350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:24.769350Z digest=sha256:38bd6e540bef2df467081f5d4f41e215a58cf2d70c2f2f30711ef4f4f72825d0

Observation 35b70089-05a0-4fa1-8c2b-22c36faedc0e · outbound

This paper cites Sparsectrl: Adding sparse controls to text-to-video diffusion models.

AnyI2V: Animating Any Conditional Image with Motion Control Sparsectrl: Adding sparse controls to text-to-video diffusion models

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:33.854495Z

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.

source=pdf_text observed=2026-08-06T20:25:24.884766Z digest=sha256:3fa51914449cbf7beb5fc0e363467c63f7480da54c67e41eaf6da711218fda02

Observation 84520573-1143-4c07-b930-d1d95e56baa1 · outbound

This paper cites CameraCtrl: Enabling Camera Control for Text-to-Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control CameraCtrl: Enabling Camera Control for Text-to-Video Generation

Reference 9

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no resolver link, observed 2026-08-06T20:25:24.979478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:24.979478Z digest=sha256:5ab3c008fbeb43b3670bb9e5ce014092fc0f87b10b689c21c02cc6a67854c5dd

Observation 00467e71-d160-4147-9adc-40188cf446b9 · outbound

This paper cites Latent Video Diffusion Models for High-Fidelity Long Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control Latent Video Diffusion Models for High-Fidelity Long Video Generation

Reference 10

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no resolver link, observed 2026-08-06T20:25:25.057827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:25.057827Z digest=sha256:3121127b5e7f0cdb3145a1bfd0d3a85cdd95595d222085ef3c208d05c37c3859

Observation c424eb1b-8aa8-43b4-960f-411cbbdaba4e · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

AnyI2V: Animating Any Conditional Image with Motion Control Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 11

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no resolver link, observed 2026-08-06T20:25:25.140993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:25.140993Z digest=sha256:cd3cd32017755330de3536fc900fc5f1d39bfae016a9001f128576c116fd85a3

Observation 4a3287ac-ad55-4777-a748-4f898526342c · outbound

This paper cites Video diffusion models.

AnyI2V: Animating Any Conditional Image with Motion Control Video diffusion models

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:33.684728Z

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.

source=pdf_text observed=2026-08-06T20:25:25.240688Z digest=sha256:0c40cba7dbc19cd8022a33eb1ca0f5bf383f5b58fa1dfa36c89ab48307c8a01f

Observation c3b78684-d66f-476e-bafb-695ab7fa9ace · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

AnyI2V: Animating Any Conditional Image with Motion Control LoRA: Low-Rank Adaptation of Large Language Models

Reference 13

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no resolver link, observed 2026-08-06T20:25:25.318105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:25.318105Z digest=sha256:2f027eadeea84847c50ee2fcdc53035e7729a00dd7f2239b93fed4c603142142

Observation 9fddd0ee-b922-46d1-9b73-51842255c65b · outbound

This paper cites Cocktail: Mixing multi-modality control for text-conditional image generation.

AnyI2V: Animating Any Conditional Image with Motion Control Cocktail: Mixing multi-modality control for text-conditional image generation

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:33.505365Z

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.

source=pdf_text observed=2026-08-06T20:25:25.380684Z digest=sha256:aa3e1f7c001bca3c9a5929bd104391c498e251067b4967dd2425ec66788591f1

Observation 475fe6c3-411c-4d7c-be8a-a8000066e717 · outbound

This paper cites VideoControlNet: A Motion-Guided Video-to-Video Translation Framework by Using Diffusion Model with ControlNet.

AnyI2V: Animating Any Conditional Image with Motion Control VideoControlNet: A Motion-Guided Video-to-Video Translation Framework by Using Diffusion Model with ControlNet

Reference 15

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no resolver link, observed 2026-08-06T20:25:25.466570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:25.466570Z digest=sha256:fb9be9c6faf55974a8f0b0690edcbee4225160bba20076af1cf350847739c5db

Observation bc66d003-8b0c-4769-bb91-666dc3eb6548 · outbound

This paper cites Arbitrary style transfer in real-time with adaptive instance normalization.

AnyI2V: Animating Any Conditional Image with Motion Control Arbitrary style transfer in real-time with adaptive instance normalization

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:33.367870Z

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.

source=pdf_text observed=2026-08-06T20:25:25.558706Z digest=sha256:8fb6f6cd146ddd37214049a900683af61d6a157480d56f97e2b5ad5f97ea0151

Observation d19d4810-6fc5-4c9f-a904-61b8c942574f · outbound

This paper cites Cotracker: It is better to track together.

AnyI2V: Animating Any Conditional Image with Motion Control Cotracker: It is better to track together

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:33.236726Z

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.

source=pdf_text observed=2026-08-06T20:25:25.679527Z digest=sha256:3a262a995c06867592c22cd5123fe03413e71201c19b4d7d51c9b6fcbcc48130

Observation 79574eae-be01-4584-ad52-ea507b4c5876 · outbound

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

AnyI2V: Animating Any Conditional Image with Motion Control Text2video-zero: Text- to-image diffusion models are zero-shot video generators

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:25.815397Z digest=sha256:2e21dffd35582850d8983da032a904719406623eab22ab72cbf4b3c8f9e3deb7

Observation b8490783-78ba-40ff-bd46-73591113df79 · outbound

This paper cites DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models.

AnyI2V: Animating Any Conditional Image with Motion Control DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models

Reference 19

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unresolved
no resolver link, observed 2026-08-06T20:25:25.914025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:25.914025Z digest=sha256:324d7d0df235b65fd899a85caf69f6ba0aacdc00f372fa8e00c2d56b4ae28c06

Observation f0a79e52-683e-471f-834b-a8b00b4bf615 · outbound

This paper cites Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis.

AnyI2V: Animating Any Conditional Image with Motion Control Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis

Reference 20

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verified exact
local_arxiv, observed 2026-08-06T20:25:29.851895Z

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.

source=pdf_text observed=2026-08-06T20:25:26.042201Z digest=sha256:58513adfb29abea08e0f8801302a893b4bb938acb25bb351a00bd81526cac266

Observation d3b52798-77ba-4689-a296-1a3266b80d7b · outbound

This paper cites Image Conductor: Precision Control for Interactive Video Synthesis.

AnyI2V: Animating Any Conditional Image with Motion Control Image Conductor: Precision Control for Interactive Video Synthesis

Reference 21

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no resolver link, observed 2026-08-06T20:25:26.170396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:26.170396Z digest=sha256:adc657d95b752b9691c97ba8ff50415a824e27d25ff1c0fc281f3eeed200fbc2

Observation 5feeba51-a878-426d-afe4-e1017b07d665 · outbound

This paper cites LOVECon: Text-driven Training-Free Long Video Editing with ControlNet.

AnyI2V: Animating Any Conditional Image with Motion Control LOVECon: Text-driven Training-Free Long Video Editing with ControlNet

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:25:29.716487Z

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.

source=pdf_text observed=2026-08-06T20:25:26.239158Z digest=sha256:f4286ebf7da473908187f6844b2513b966377006acfd9980476506ed3fd0b421

Observation 00524d34-72b6-4ca3-a573-6b5d1407a5dc · outbound

This paper cites Trailblazer: Trajectory control for diffusion-based video generation.

AnyI2V: Animating Any Conditional Image with Motion Control Trailblazer: Trajectory control for diffusion-based video generation

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:33.012633Z

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.

source=pdf_text observed=2026-08-06T20:25:26.320914Z digest=sha256:88861cf91bacf3084f8cf10b224654b62b00d03ca9f342b80efbd4b6d0075926

Observation e796bd06-2fb9-498a-8b85-e3ccb432bbb7 · outbound

This paper cites Some methods for classification and analysis of multivariate observations.

AnyI2V: Animating Any Conditional Image with Motion Control Some methods for classification and analysis of multivariate observations

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-06T20:25:32.881148Z

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.

source=pdf_text observed=2026-08-06T20:25:26.403459Z digest=sha256:323706bf8f79e8e82ef9e4a9c17e32b120aab011f436cec6a021781bbcbc739b

Observation 661d2f45-91d9-4fc7-9bda-a2cced54d8c5 · outbound

This paper cites Large-scale video panoptic segmentation in the wild: A benchmark.

AnyI2V: Animating Any Conditional Image with Motion Control Large-scale video panoptic segmentation in the wild: A benchmark

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:32.735514Z

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.

source=pdf_text observed=2026-08-06T20:25:26.474151Z digest=sha256:53cfd41e908de3cfbf8f9cd3d996e48d9ae35125f26e1c9a778bf6712ca76d4b

Observation d73ee21d-b3cd-43af-97c1-0bea7ea1e6ca · outbound

This paper cites Freecontrol: Training-free spatial control of any text-to-image diffusion model with any condition.

AnyI2V: Animating Any Conditional Image with Motion Control Freecontrol: Training-free spatial control of any text-to-image diffusion model with any condition

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:32.562331Z

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.

source=pdf_text observed=2026-08-06T20:25:26.553258Z digest=sha256:7b956a7bb33c67efadfd8dcb3ac7980feae83fcab4fcb1cc11422450560c5d2d

Observation 8526d6aa-bf06-4f6b-85a0-d2c9887d5ca2 · outbound

This paper cites SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control SG-I2V: Self-Guided Trajectory Control in Image-to-Video Generation

Reference 27

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no resolver link, observed 2026-08-06T20:25:26.611739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:26.611739Z digest=sha256:3b1cca54b39c3f4607f6f16f8836d227ba8d4c77cef06dc266ea38caf2a9817d

Observation 0afba912-7f85-4603-bfd0-d1ec67db126d · outbound

This paper cites Mofa-video: Controllable image animation via generative motion field adaptions in frozen image-to-video diffusion model.

AnyI2V: Animating Any Conditional Image with Motion Control Mofa-video: Controllable image animation via generative motion field adaptions in frozen image-to-video diffusion model

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:32.433431Z

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.

source=pdf_text observed=2026-08-06T20:25:26.685839Z digest=sha256:487cbc5a3dfc3e14adb5efcf050185c0942f4a2affefcd8ded093c26853e3eaa

Observation 92e86803-561b-43a2-b383-9cdfb26ad7d8 · outbound

This paper cites Drag your gan: Interactive point-based manipulation on the generative image manifold.

AnyI2V: Animating Any Conditional Image with Motion Control Drag your gan: Interactive point-based manipulation on the generative image manifold

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:32.218979Z

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.

source=pdf_text observed=2026-08-06T20:25:26.760190Z digest=sha256:dfe713e0b878c5e97c36f372683228ec8d5e87cad71095cfb6106adedfc569f8

Observation 38b44cb9-bcc3-40a5-8436-4c7176e5d212 · outbound

This paper cites UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild.

AnyI2V: Animating Any Conditional Image with Motion Control UniControl: A Unified Diffusion Model for Controllable Visual Generation In the Wild

Reference 30

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unresolved
no resolver link, observed 2026-08-06T20:25:26.818684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:26.818684Z digest=sha256:20005f7585496db2ed9e5b1d349e4ca39b46d1bf6c0fe4083e49e82e08e009a6

Observation 42402254-5ab4-4997-be70-b199df2bf15c · outbound

This paper cites FreeTraj: Tuning-Free Trajectory Control in Video Diffusion Models.

AnyI2V: Animating Any Conditional Image with Motion Control FreeTraj: Tuning-Free Trajectory Control in Video Diffusion Models

Reference 31

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unresolved
no resolver link, observed 2026-08-06T20:25:26.881733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:26.881733Z digest=sha256:e33f8092dce377b78296d189ca665c6a8715a718eb73074162c02e1b5d8eaa21

Observation baed88d4-efb6-4686-a27d-15a66c5355a1 · outbound

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

AnyI2V: Animating Any Conditional Image with Motion Control High-resolution image synthesis with latent diffusion models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:26.900124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:26.900124Z digest=sha256:86bcfe953415624054dca5db504fe7de407aa5ca43a99af5c5498cdc619bbc08

Observation fd175d70-34e2-448a-b6f4-b2577bf1b0ce · outbound

This paper cites Motion-i2v: Consistent and controllable image-to-video generation with explicit motion modeling.

AnyI2V: Animating Any Conditional Image with Motion Control Motion-i2v: Consistent and controllable image-to-video generation with explicit motion modeling

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:32.068727Z

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.

source=pdf_text observed=2026-08-06T20:25:26.970264Z digest=sha256:f7b40d68d8548470a37fe60a35b64d30c438ded47db14ef0b7b099dfbeb3a3b4

Observation 15eb4f40-dd58-403c-b2c4-ed011779c61b · outbound

This paper cites Dragdiffusion: Harnessing diffusion models for interactive point-based image editing.

AnyI2V: Animating Any Conditional Image with Motion Control Dragdiffusion: Harnessing diffusion models for interactive point-based image editing

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:31.963843Z

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.

source=pdf_text observed=2026-08-06T20:25:27.078636Z digest=sha256:6eeb3db95d11ae90da01f194df714ae8cd69a1ef965b07aceace33f28418542d

Observation 40b743f7-bc70-444f-8b57-053c8fc6fc83 · outbound

This paper cites A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models.

AnyI2V: Animating Any Conditional Image with Motion Control A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models

Reference 35

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no resolver link, observed 2026-08-06T20:25:27.267209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.267209Z digest=sha256:24c5072b80949a07977d6592e908be9f2a200f01e4d54cb103a389a6aed26a46

Observation 32df7593-0501-4d21-bc58-60be5e71da60 · outbound

This paper cites Free-form motion control: A synthetic video generation dataset with controllable camera and object motions.

AnyI2V: Animating Any Conditional Image with Motion Control Free-form motion control: A synthetic video generation dataset with controllable camera and object motions

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.408167Z digest=sha256:461386d83b1d14a682017582c951170056f13a64f35d5cc6d205220de6225a76

Observation d3201c98-aac7-4366-8a95-f8f259a0d87d · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

AnyI2V: Animating Any Conditional Image with Motion Control Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:27.446167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.446167Z digest=sha256:2bb229f91cd6326e6e90cd3db7fcd33db453020988c63282430d596dc06d2fba

Observation b5292019-0b83-4721-be2b-ae7ff2d5fb28 · outbound

This paper cites Denoising Diffusion Implicit Models.

AnyI2V: Animating Any Conditional Image with Motion Control Denoising Diffusion Implicit Models

Reference 38

Resolution
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no resolver link, observed 2026-08-06T20:25:27.533479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.533479Z digest=sha256:b9524cf37fa77dd00daabaf01f140210cc80dd6fec667081559f9621752c6266

Observation f6a8d720-8439-483d-a44e-83d33bed5481 · outbound

This paper cites Anycontrol: create your artwork with versatile control on text-to-image generation.

AnyI2V: Animating Any Conditional Image with Motion Control Anycontrol: create your artwork with versatile control on text-to-image generation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:31.798937Z

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.

source=pdf_text observed=2026-08-06T20:25:27.623943Z digest=sha256:dabf8e767e19582c96b0fa05ffeefb381ce8bf3d5785c602e1d4df750617ad22

Observation 27c0b93b-146f-400e-91c5-0aa28818b3fd · outbound

This paper cites Plug-and-play diffusion features for text-driven image-to-image translation.

AnyI2V: Animating Any Conditional Image with Motion Control Plug-and-play diffusion features for text-driven image-to-image translation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:31.654118Z

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.

source=pdf_text observed=2026-08-06T20:25:27.774197Z digest=sha256:79eaeb0ee42f567366a87c2ce7ad25ccb3e32e676d356fef93302c3477fab621

Observation d3771b2c-ec8f-4c5b-af71-83e19304621e · outbound

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

AnyI2V: Animating Any Conditional Image with Motion Control ModelScope Text-to-Video Technical Report

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:27.903864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:27.903864Z digest=sha256:4d9ebb931026f2c43e1ca9ecaf7af26985f6be005e274b05e3d2e01984bc47d8

Observation ef2b81e3-e487-4b92-a6da-fb15b3fc5765 · outbound

This paper cites Boximator: Generating Rich and Controllable Motions for Video Synthesis.

AnyI2V: Animating Any Conditional Image with Motion Control Boximator: Generating Rich and Controllable Motions for Video Synthesis

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:28.032439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:28.032439Z digest=sha256:3de5d6209046ebeaa83702c89659bbcd2df924ce4332b17677ca5c95eb51889f

Observation d856d6b6-8afc-4eee-a71d-a74b60ec6519 · outbound

This paper cites Videocomposer: Compositional video synthesis with motion controllability.

AnyI2V: Animating Any Conditional Image with Motion Control Videocomposer: Compositional video synthesis with motion controllability

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:31.526763Z

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.

source=pdf_text observed=2026-08-06T20:25:28.197918Z digest=sha256:da2fca3329fdd7f4db1faacdebaf6d26d4283454775ba135c70f4baa75ba32a5

Observation 37898861-1e15-4fec-b544-e391ee84143d · outbound

This paper cites Lavie: High-quality video generation with cascaded latent diffusion models.

AnyI2V: Animating Any Conditional Image with Motion Control Lavie: High-quality video generation with cascaded latent diffusion models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:31.177524Z

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.

source=pdf_text observed=2026-08-06T20:25:28.282240Z digest=sha256:917973be10280813866c9b61629dc2c11e1ae9a8849d1aad28fd8635618a6d78

Observation c9840de4-56e8-4fd6-9acd-8ff050e23d5c · outbound

This paper cites ObjCtrl-2.5D: Training-free Object Control with Camera Poses.

AnyI2V: Animating Any Conditional Image with Motion Control ObjCtrl-2.5D: Training-free Object Control with Camera Poses

Reference 45

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unresolved
no resolver link, observed 2026-08-06T20:25:28.341243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:28.341243Z digest=sha256:4d39672e573ec3fa5727d8b2658167fd45cb60bddeab6ae15b8a3bccda01bfca

Observation 91b33beb-3f62-4ddb-969e-f0e49dd75f68 · outbound

This paper cites Motionctrl: A unified and flexible motion controller for video generation.

AnyI2V: Animating Any Conditional Image with Motion Control Motionctrl: A unified and flexible motion controller for video generation

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:30.904545Z

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.

source=pdf_text observed=2026-08-06T20:25:28.415133Z digest=sha256:ec0ba16c00775e8635f1fb872b1a0313aebcaf0e1b239bc101c7409fe9221df9

Observation 396d7879-b606-43e1-a74c-6cba50ac1ae1 · outbound

This paper cites Principal component analysis.

AnyI2V: Animating Any Conditional Image with Motion Control Principal component analysis

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:30.631228Z

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.

source=pdf_text observed=2026-08-06T20:25:28.525885Z digest=sha256:249ba4dcddc5aaa9585bb3a0ff0106b9bd908d4aa09fcaa71d46bb0d64b7ada1

Observation 39f036ab-5588-464d-8392-59af76ab3bf2 · outbound

This paper cites MotionBooth: Motion-Aware Customized Text-to-Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control MotionBooth: Motion-Aware Customized Text-to-Video Generation

Reference 48

Resolution
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no resolver link, observed 2026-08-06T20:25:28.608683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:28.608683Z digest=sha256:9f910cb647df5dcb4a41000ac6fb6ec81158f20369048d99781189597a04da8b

Observation 15b79da1-3c97-477f-b11c-507de6af68ec · outbound

This paper cites Draganything: Motion control for anything using entity representation.

AnyI2V: Animating Any Conditional Image with Motion Control Draganything: Motion control for anything using entity representation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:30.383936Z

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.

source=pdf_text observed=2026-08-06T20:25:28.647601Z digest=sha256:ea2b37af5284727411fa9aa4a094c80bb14417832b6889e51bc9ca83ea717b7a

Observation d8787f87-8def-4463-8b24-f76278b73f0c · outbound

This paper cites Video Diffusion Models are Training-free Motion Interpreter and Controller.

AnyI2V: Animating Any Conditional Image with Motion Control Video Diffusion Models are Training-free Motion Interpreter and Controller

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:28.728755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:28.728755Z digest=sha256:9d348ed8d93908be1362dccdb76937bec7dab8362cf39eda8c6e413276ae1e4c

Observation 4ab67a9c-61ea-49c4-a657-7d1bc1f651b0 · outbound

This paper cites Dynamicrafter: Animating open-domain images with video diffusion priors.

AnyI2V: Animating Any Conditional Image with Motion Control Dynamicrafter: Animating open-domain images with video diffusion priors

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:28.790311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:28.790311Z digest=sha256:8319f3d2d6b1b0e95d4068f343d88bc548fbf73d86cbb933e9a88a0e06a68445

Observation ec32a8f0-e334-4054-882a-570f449f538f · outbound

This paper cites Direct-a-video: Customized video generation with user- directed camera movement and object motion.

AnyI2V: Animating Any Conditional Image with Motion Control Direct-a-video: Customized video generation with user- directed camera movement and object motion

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T20:25:30.116321Z

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.

source=pdf_text observed=2026-08-06T20:25:28.847157Z digest=sha256:092b36fcd28a642c35f1e8d3d4e4bb63ab9fe3268bc4d7c44188dafc1d8ecf39

Observation 695822a8-cc50-409c-8cf6-d9736a99a273 · outbound

This paper cites DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory.

AnyI2V: Animating Any Conditional Image with Motion Control DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:28.946126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:28.946126Z digest=sha256:c9754774c2b038b932b99f3c59de480e49f4c511d6bcd2061c006baa2411986f

Observation 5b748225-0f62-4468-8f00-57e762518ba8 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

AnyI2V: Animating Any Conditional Image with Motion Control Adding conditional control to text-to-image diffusion models

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:28.992068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:28.992068Z digest=sha256:f5fa8b8ba3730683fb9d62e25789c3ae4188e50ad351a8c9a317a429ab719081

Observation 1dc34cde-99a8-4f00-8daa-3face3f52316 · outbound

This paper cites ControlVideo: Training-free Controllable Text-to-Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control ControlVideo: Training-free Controllable Text-to-Video Generation

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:29.057301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:29.057301Z digest=sha256:bf5049d33d20c8ba6040aba880e84cbdcb8cfd833d62e85d4cf1eef12f0755ff

Observation 1351d6ee-1961-4baa-95d3-85db563283d7 · outbound

This paper cites Tora: Trajectory-oriented Diffusion Transformer for Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control Tora: Trajectory-oriented Diffusion Transformer for Video Generation

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T20:25:29.127199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:25:29.127199Z digest=sha256:756964a19a52b60846927159babeec8095c32df7ec77dbaf4c18406246ec8bc4

Observation cdcdc99d-47e6-4ea1-8476-9548690d5220 · outbound

This paper cites TrackGo: A Flexible and Efficient Method for Controllable Video Generation.

AnyI2V: Animating Any Conditional Image with Motion Control TrackGo: A Flexible and Efficient Method for Controllable Video Generation

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:25:29.416173Z

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.

source=pdf_text observed=2026-08-06T20:25:29.212390Z digest=sha256:2e21e92edf50f9f2fe4718bc0bc2d60bbd954e624d4904a6fd294528334b2f1a

Pith citing papers

Observation bd2c33f3-ad0b-4654-8b84-00132bccf2f5 · inbound

QWERTY: Training-Free Motion Control via Query-Warped Video Diffusion Transformers cites this paper.

QWERTY: Training-Free Motion Control via Query-Warped Video Diffusion Transformers AnyI2V: Animating Any Conditional Image with Motion Control

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:28:38.520077Z

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.

source=pdf_text observed=2026-07-03T16:19:51.348169Z digest=sha256:5b114c7bf6334c621eef8eefff490699b1d01eafb4760f1e7e43c3430f3a66fa