Saved in:
| Main Authors: | He, Haoran, Zhang, Yang, Lin, Liang, Xu, Zhongwen, Pan, Ling |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.07825 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Scaling Image and Video Generation via Test-Time Evolutionary Search
by: He, Haoran, et al.
Published: (2025)
by: He, Haoran, et al.
Published: (2025)
Rethinking Video Generation Model for the Embodied World
by: Deng, Yufan, et al.
Published: (2026)
by: Deng, Yufan, et al.
Published: (2026)
Luminark: Training-free, Probabilistically-Certified Watermarking for General Vision Generative Models
by: Xu, Jiayi, et al.
Published: (2026)
by: Xu, Jiayi, et al.
Published: (2026)
WorldModelBench: Judging Video Generation Models As World Models
by: Li, Dacheng, et al.
Published: (2025)
by: Li, Dacheng, et al.
Published: (2025)
Physical Simulator In-the-Loop Video Generation
by: Foo, Lin Geng, et al.
Published: (2026)
by: Foo, Lin Geng, et al.
Published: (2026)
Seaweed-7B: Cost-Effective Training of Video Generation Foundation Model
by: Seawead, Team, et al.
Published: (2025)
by: Seawead, Team, et al.
Published: (2025)
How Far is Video Generation from World Model: A Physical Law Perspective
by: Kang, Bingyi, et al.
Published: (2024)
by: Kang, Bingyi, et al.
Published: (2024)
S2DM: Sector-Shaped Diffusion Models for Video Generation
by: Lang, Haoran, et al.
Published: (2024)
by: Lang, Haoran, et al.
Published: (2024)
Medical Video Generation for Disease Progression Simulation
by: Cao, Xu, et al.
Published: (2024)
by: Cao, Xu, et al.
Published: (2024)
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Models
by: Shi, Fengyuan, et al.
Published: (2023)
by: Shi, Fengyuan, et al.
Published: (2023)
ShareVerse: Multi-Agent Consistent Video Generation for Shared World Modeling
by: Zhu, Jiayi, et al.
Published: (2026)
by: Zhu, Jiayi, et al.
Published: (2026)
EditWorld: Simulating World Dynamics for Instruction-Following Image Editing
by: Yang, Ling, et al.
Published: (2024)
by: Yang, Ling, et al.
Published: (2024)
Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation
by: Inferix Team, et al.
Published: (2025)
by: Inferix Team, et al.
Published: (2025)
Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey
by: Fu, Ao, et al.
Published: (2024)
by: Fu, Ao, et al.
Published: (2024)
Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
by: Wang, Ye, et al.
Published: (2025)
by: Wang, Ye, et al.
Published: (2025)
RISE-Video: Can Video Generators Decode Implicit World Rules?
by: Liu, Mingxin, et al.
Published: (2026)
by: Liu, Mingxin, et al.
Published: (2026)
A Mechanistic View on Video Generation as World Models: State and Dynamics
by: Wang, Luozhou, et al.
Published: (2026)
by: Wang, Luozhou, et al.
Published: (2026)
World Simulation with Video Foundation Models for Physical AI
by: NVIDIA, et al.
Published: (2025)
by: NVIDIA, et al.
Published: (2025)
HARIVO: Harnessing Text-to-Image Models for Video Generation
by: Kwon, Mingi, et al.
Published: (2024)
by: Kwon, Mingi, et al.
Published: (2024)
Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild
by: Wen, Zhuofan, et al.
Published: (2024)
by: Wen, Zhuofan, et al.
Published: (2024)
VRAG: Learning World Models for Interactive Video Generation
by: Chen, Taiye, et al.
Published: (2025)
by: Chen, Taiye, et al.
Published: (2025)
Refining Pre-Trained Motion Models
by: Sun, Xinglong, et al.
Published: (2024)
by: Sun, Xinglong, et al.
Published: (2024)
AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
by: Wang, Zun, et al.
Published: (2026)
by: Wang, Zun, et al.
Published: (2026)
Pre-Trained Vision-Language Models as Partial Annotators
by: Wang, Qian-Wei, et al.
Published: (2024)
by: Wang, Qian-Wei, et al.
Published: (2024)
VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation
by: He, Xuan, et al.
Published: (2024)
by: He, Xuan, et al.
Published: (2024)
HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
by: Liu, Han, et al.
Published: (2026)
by: Liu, Han, et al.
Published: (2026)
Efficient Training of Large Vision Models via Advanced Automated Progressive Learning
by: Li, Changlin, et al.
Published: (2024)
by: Li, Changlin, et al.
Published: (2024)
Pre-Trained CNN Architecture for Transformer-Based Image Caption Generation Model
by: Dufera, Amanuel Tafese
Published: (2025)
by: Dufera, Amanuel Tafese
Published: (2025)
GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model
by: Yu, Caiyang, et al.
Published: (2023)
by: Yu, Caiyang, et al.
Published: (2023)
Autoregressive Adversarial Post-Training for Real-Time Interactive Video Generation
by: Lin, Shanchuan, et al.
Published: (2025)
by: Lin, Shanchuan, et al.
Published: (2025)
Contextualized Diffusion Models for Text-Guided Image and Video Generation
by: Yang, Ling, et al.
Published: (2024)
by: Yang, Ling, et al.
Published: (2024)
Open-Sora Plan: Open-Source Large Video Generation Model
by: Lin, Bin, et al.
Published: (2024)
by: Lin, Bin, et al.
Published: (2024)
OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?
by: Li, Yifei, et al.
Published: (2025)
by: Li, Yifei, et al.
Published: (2025)
Efficient Training for Human Video Generation with Entropy-Guided Prioritized Progressive Learning
by: Li, Changlin, et al.
Published: (2025)
by: Li, Changlin, et al.
Published: (2025)
Chain-of-Models Pre-Training: Rethinking Training Acceleration of Vision Foundation Models
by: Fan, Jiawei, et al.
Published: (2026)
by: Fan, Jiawei, et al.
Published: (2026)
EgoSim: Egocentric World Simulator for Embodied Interaction Generation
by: Hao, Jinkun, et al.
Published: (2026)
by: Hao, Jinkun, et al.
Published: (2026)
D3: Training-Free AI-Generated Video Detection Using Second-Order Features
by: Zheng, Chende, et al.
Published: (2025)
by: Zheng, Chende, et al.
Published: (2025)
Simulating the Real World: A Unified Survey of Multimodal Generative Models
by: Hu, Yuqi, et al.
Published: (2025)
by: Hu, Yuqi, et al.
Published: (2025)
Geometry Forcing: Marrying Video Diffusion and 3D Representation for Consistent World Modeling
by: Wu, Haoyu, et al.
Published: (2025)
by: Wu, Haoyu, et al.
Published: (2025)
RelightVid: Temporal-Consistent Diffusion Model for Video Relighting
by: Fang, Ye, et al.
Published: (2025)
by: Fang, Ye, et al.
Published: (2025)
Similar Items
-
Scaling Image and Video Generation via Test-Time Evolutionary Search
by: He, Haoran, et al.
Published: (2025) -
Rethinking Video Generation Model for the Embodied World
by: Deng, Yufan, et al.
Published: (2026) -
Luminark: Training-free, Probabilistically-Certified Watermarking for General Vision Generative Models
by: Xu, Jiayi, et al.
Published: (2026) -
WorldModelBench: Judging Video Generation Models As World Models
by: Li, Dacheng, et al.
Published: (2025) -
Physical Simulator In-the-Loop Video Generation
by: Foo, Lin Geng, et al.
Published: (2026)