Research collection

Video generation and world models

Generating or simulating video: long-form and interactive video generation, controllable video synthesis, and generative video world models.

Papers: 106
Research labs: 3
Official code: 82

101–106 of 106 papers in this collection

101

arXiv.org

3D and 4D World Modeling: A Survey

This survey provides the first comprehensive review of 3D and 4D world modeling, addressing the lack of standardized definitions and the fragmented literature that often focuses on 2D generative methods. It establishes precise definitions and a hierarchical taxonomy categorizing methods into video-based (VideoGen), occupancy-based (OccGen), and LiDAR-based…

Lingdong Kong, Yu Yang, Jianbiao Mei, Youquan Liu, et al.

Published: Sep 2025
Citations: 65
Code: 960 stars

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102

arXiv.org

4DNeX: Feed-Forward 4D Generative Modeling Made Easy

4DNeX is the first feed-forward framework for generating 4D (dynamic 3D) scene representations from a single image. It fine-tunes a pretrained video diffusion model (Wan2.1) to generate a unified 6D video representation (RGB and XYZ sequences) jointly, enabling efficient end-to-end image-to-4D generation. To address data scarcity, the authors constructed…

Zhaoxi Chen, Tianqi Liu, Long Zhuo, Jiawei Ren, et al.

Published: Aug 2025
Citations: 31
Code: 840 stars

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103

arXiv.org

ToonComposer: Streamlining Cartoon Production with Generative Post-Keyframing

ToonComposer is a generative model that unifies the traditionally separate inbetweening and colorization stages of cartoon production into a single post-keyframing stage. Built on the DiT-based video foundation model Wan 2.1, it uses a sparse sketch injection mechanism for precise control from keyframe sketches and a spatial low-rank adapter (SLRA) to…

Lingen Li, Guangzhi Wang, Zhaoyang Zhang, Yaowei Li, et al.

Published: Aug 2025
Citations: 8
Code: 584 stars

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104

arXiv.org

Matrix-3D: Omnidirectional Explorable 3D World Generation

Matrix-3D is a framework for generating omnidirectional, explorable 3D worlds from a single image or text prompt. It uses panoramic representations to overcome the limited field of view of perspective-based methods. The pipeline first generates a panorama image, then a trajectory-guided panoramic video using a diffusion model conditioned on scene mesh…

Zhongqi Yang, Wenhang Ge, Yuqi Li, Jiaqi Chen, et al.

Published: Aug 2025
Citations: 28
Code: 777 stars

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105

AAAI Conference on Artificial Intelligence

Omni-Effects: Unified and Spatially-Controllable Visual Effects Generation

Omni-Effects is a unified framework for generating spatially controllable visual effects (VFX) in videos, addressing limitations of existing per-effect LoRA training. It introduces two key innovations: LoRA-based Mixture of Experts (LoRA-MoE) to integrate diverse effects in a single model while mitigating cross-task interference, and Spatial-Aware Prompt…

Fangyuan Mao, Aiming Hao, Jintao Chen, Dongxia Liu, et al.

Published: Aug 2025
Citations: 28
Code: 175 stars

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106

arXiv.org

LongVie: Multimodal-Guided Controllable Ultra-Long Video Generation

LongVie is a framework for controllable ultra-long video generation, addressing temporal inconsistency and visual degradation in autoregressive generation. It identifies three key issues: separate noise initialization, independent control signal normalization, and single-modality guidance limitations. LongVie introduces unified noise initialization and…

Jianxiong Gao, Zhaoxi Chen, Xian Liu, Jianfeng Feng, et al.

Published: Aug 2025
Citations: 19
Code: Not linked

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