Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation | Paper Citation Record

Observation 0c5b3160-2dd4-4777-b2c2-027c58e70c39 · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Cosmos World Foundation Model Platform for Physical AI

Reference 1

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Observation 2acf383b-1666-48ee-be86-55603b2dd5ed · outbound

This paper cites Lyra: Generative 3d scene reconstruction via video diffusion model self-distillation.arXiv preprint arXiv:2509.19296, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Lyra: Generative 3d scene reconstruction via video diffusion model self-distillation.arXiv preprint arXiv:2509.19296, 2025

Reference 2

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Observation b641051e-0a8c-4eb3-9912-f373fb6cf71d · outbound

This paper cites Ac3d: Analyzing and improving 3d camera control in video diffusion transformers.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Ac3d: Analyzing and improving 3d camera control in video diffusion transformers

Reference 3

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Observation 3e125f6e-a77a-41c1-be79-5bfb4e0de332 · outbound

This paper cites Recammaster: Camera-controlled generative rendering from a single video.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Recammaster: Camera-controlled generative rendering from a single video

Reference 4

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Observation 7eb32241-8999-47f7-8283-5cd6edb5d393 · outbound

This paper cites Qwen3-VL Technical Report.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Qwen3-VL Technical Report

Reference 5

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Observation 1916d094-f247-46e0-b8e0-121ae6c6bba7 · outbound

This paper cites Lumiere: A space-time diffusion model for video generation.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Lumiere: A space-time diffusion model for video generation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation e3264584-a0c6-452c-b2f2-d9e6b874fa45 · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 7

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Observation 86c19943-ad26-4468-a2f4-77e5f4980a5e · outbound

This paper cites Go-with-the-flow: Motion-controllable video diffusion models using real-time warped noise.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Go-with-the-flow: Motion-controllable video diffusion models using real-time warped noise

Reference 8

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Observation 70f3f905-a710-4e55-b059-1847a665ae96 · outbound

This paper cites Sam 3: Segment anything with concepts, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Sam 3: Segment anything with concepts, 2025

Reference 9

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Observation 51a09343-a29c-4bbb-9f74-81f8b5eceabc · outbound

This paper cites How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models

Reference 10

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Observation ece77e36-243e-471c-8e05-7441f64a3e8c · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Reference 11

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Observation a4730138-7323-4bcb-83c1-293edea95b5a · outbound

This paper cites 4DNeX: Feed-Forward 4D Generative Modeling Made Easy.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation 4DNeX: Feed-Forward 4D Generative Modeling Made Easy

Reference 12

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Observation 407f18e2-e538-4a5b-9ac8-4f788df9a69e · outbound

This paper cites Wan-move: Motion-controllable video generation via latent trajectory guidance.arXiv preprint arXiv:2512.08765, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Wan-move: Motion-controllable video generation via latent trajectory guidance.arXiv preprint arXiv:2512.08765, 2025

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 2fbf486a-373f-4d67-888f-18b8405b9abd · outbound

This paper cites Motion prompting: Controlling video generation with motion trajectories.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Motion prompting: Controlling video generation with motion trajectories

Reference 14

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Observation cfd1c376-f6d0-4460-929e-b706338f01cd · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning

Reference 15

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Observation e7d3c7bc-f0c7-4514-8097-1c909f20e680 · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation CameraCtrl: Enabling Camera Control for Text-to-Video Generation

Reference 16

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Observation 703a391a-a37e-4ba0-83b4-572037be1f9c · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation feb6f807-ca5d-4bc5-a14a-5b9f004604f4 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Imagen Video: High Definition Video Generation with Diffusion Models

Reference 18

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Observation 6b1371f9-0397-4373-9c4f-819c0fca6059 · outbound

This paper cites Video diffusion models.Advances in neural information processing systems, 35:8633–8646, 2022.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Video diffusion models.Advances in neural information processing systems, 35:8633–8646, 2022

Reference 19

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Observation 65206bb5-844d-4088-921b-9baf1ed6c28e · outbound

This paper cites CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers

Reference 20

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Observation 74be7222-a4a7-4a15-bf15-aac8749fd7fb · outbound

This paper cites Training-free Camera Control for Video Generation.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Training-free Camera Control for Video Generation

Reference 21

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Observation 73d02371-1657-4b9d-8436-ca6763d504ee · outbound

This paper cites ViPE: Video Pose Engine for 3D Geometric Perception.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation ViPE: Video Pose Engine for 3D Geometric Perception

Reference 22

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Observation 22473f04-39b6-4ec6-8556-bfabd0a5e742 · outbound

This paper cites VBench: Comprehensive benchmark suite for video generative models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation VBench: Comprehensive benchmark suite for video generative models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 3bec5d97-9536-436f-ab92-fd30d0e71ac3 · outbound

This paper cites Peekaboo: Interactive video generation via masked-diffusion.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Peekaboo: Interactive video generation via masked-diffusion

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 05bec61a-6350-44a1-9b1e-966ccdff0e58 · outbound

This paper cites DreamGen: Unlocking Generalization in Robot Learning through Video World Models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation DreamGen: Unlocking Generalization in Robot Learning through Video World Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 9afa2aaa-4d8e-470a-8a73-d3a281b01f98 · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954, 2024.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Pyramidal flow matching for efficient video generative modeling.arXiv preprint arXiv:2410.05954, 2024

Reference 26

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Observation 695fd7fd-212c-4636-827b-3b06473144c3 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation f22cab89-9c06-4c00-a878-9e1f02775833 · outbound

This paper cites Onlyflow: Optical flow based motion conditioning for video diffusion models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Onlyflow: Optical flow based motion conditioning for video diffusion models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 81bd0689-798f-4406-b272-856ada0379a8 · outbound

This paper cites Collaborative video diffusion: Consistent multi-video generation with camera control.Advances in Neural Information Processing Systems, 37:16240–16271, 2024.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Collaborative video diffusion: Consistent multi-video generation with camera control.Advances in Neural Information Processing Systems, 37:16240–16271, 2024

Reference 29

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Observation 4b5b06eb-a6ac-413f-81d7-0ff230f387c0 · outbound

This paper cites Generative video motion editing with 3d point tracks.arXiv preprint arXiv:2512.02015, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Generative video motion editing with 3d point tracks.arXiv preprint arXiv:2512.02015, 2025

Reference 30

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Observation d603109c-e3d0-4ab1-9299-118e7f956575 · outbound

This paper cites Magicmotion: Controllable video generation with dense-to-sparse trajectory guidance.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Magicmotion: Controllable video generation with dense-to-sparse trajectory guidance

Reference 31

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Observation ea473683-9219-419a-9f9a-e61d98aaf9eb · outbound

This paper cites Lightx2v: Light video generation inference framework, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Lightx2v: Light video generation inference framework, 2025

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation fa29b8e1-86c8-48a8-8ae1-3dd27b661827 · outbound

This paper cites Equivdm: Equivariant video diffusion models with temporally consistent noise.arXiv e-prints, pages arXiv–2504, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Equivdm: Equivariant video diffusion models with temporally consistent noise.arXiv e-prints, pages arXiv–2504, 2025

Reference 33

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Observation 5113146b-456b-4fdf-9c93-1267d0a926f0 · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Movie Gen: A Cast of Media Foundation Models

Reference 34

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Observation b4a56b0e-7fe3-4e36-ab01-f2db7e19be6c · outbound

This paper cites Gen3c: 3d-informed world-consistent video generation with precise camera control.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Gen3c: 3d-informed world-consistent video generation with precise camera control

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 51601bb5-7897-4c56-a2f6-e7521b157b60 · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Motion-i2v: Consistent and controllable image-to-video generation with explicit motion modeling

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 58dc2b39-5002-428e-a2bd-069cb12f884c · outbound

This paper cites Time-to-move: Training-free motion controlled video generation via dual-clock denoising.arXiv preprint arXiv:2511.08633, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Time-to-move: Training-free motion controlled video generation via dual-clock denoising.arXiv preprint arXiv:2511.08633, 2025

Reference 37

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Observation d44843bb-e773-42ef-983a-26ebb887df8e · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Raft: Recurrent all-pairs field transforms for optical flow

Reference 38

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Observation 632c60db-386a-4d2b-aec6-f59547fb8136 · outbound

This paper cites Fvd: A new metric for video generation.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Fvd: A new metric for video generation

Reference 39

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Observation ebd2bae2-5ce3-4c8b-ac87-8e2d1c144cd1 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Wan: Open and Advanced Large-Scale Video Generative Models

Reference 40

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Observation a4d8813f-a48a-487f-81f6-59208c30e90e · outbound

This paper cites Robovip: Multi-view video generation with visual identity prompting augments robot manipulation.arXiv preprint arXiv:2601.05241, 2026.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Robovip: Multi-view video generation with visual identity prompting augments robot manipulation.arXiv preprint arXiv:2601.05241, 2026

Reference 41

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Observation 65de68b2-de68-4171-9f69-876352185803 · outbound

This paper cites Levitor: 3d trajectory oriented image-to-video synthesis.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Levitor: 3d trajectory oriented image-to-video synthesis

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Observation 16115d73-5927-4423-a3f7-e5c24680bd0c · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Boximator: Generating Rich and Controllable Motions for Video Synthesis

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Observation 9b199c29-e82c-48e4-ba11-dc029e30ce60 · outbound

This paper cites Image conductor: Precision control for interactive video synthesis.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Image conductor: Precision control for interactive video synthesis

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Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation b1a8f105-073b-413f-a437-3a1c80d0c499 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004

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Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation f066048a-fac3-4292-9a23-61263c0af386 · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Motionctrl: A unified and flexible motion controller for video generation

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Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation d76225e9-23bf-4483-83fc-7dc7cb722450 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-12T06:59:31.137097Z

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Observation 7414f65e-f947-40c3-8bd3-f2ea93f5b4c4 · outbound

This paper cites Dynamic View Synthesis as an Inverse Problem.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Dynamic View Synthesis as an Inverse Problem

Reference 48

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Observation 07a59c49-ed3d-4067-a4aa-1bc745b5babd · outbound

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

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory

Reference 49

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Observation 338a55f1-5809-4df3-b23c-579a3204784d · outbound

This paper cites Tapip3d: Tracking any point in persistent 3d geometry.arXiv preprint arXiv:2504.14717, 2025.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Tapip3d: Tracking any point in persistent 3d geometry.arXiv preprint arXiv:2504.14717, 2025

Reference 50

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Observation 21844aa5-deb3-4a9c-9f6f-9206579173a2 · outbound

This paper cites Tora: Trajectory-oriented diffusion transformer for video generation.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Tora: Trajectory-oriented diffusion transformer for video generation

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Observation dc9a7e76-ad6f-4168-a52f-528ff6d6a194 · outbound

This paper cites Versecrafter: Dynamic realistic video world model with 4d geometric control.arXiv preprint arXiv:2601.05138, 2026.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Versecrafter: Dynamic realistic video world model with 4d geometric control.arXiv preprint arXiv:2601.05138, 2026

Reference 52

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Observation 244fa066-15e4-40cf-bd5c-ccf81db97a5d · outbound

This paper cites Posecrafter: One-shot personalized video synthesis following flexible pose control.

Track the Noise, Move the World:3D-Grounded Motion-Consistent Noise for Controllable Video Generation Posecrafter: One-shot personalized video synthesis following flexible pose control

Reference 53

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