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20232026
most citedOccWorld: Learning a 3D Occupancy World Model for Autonomous Driving

5 citations · 7 across the 9 of their papers we have counts for

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cs.CV2026

Moaw: Unleashing Motion Awareness for Video Diffusion Models

Tianqi Zhang, Ziyi Wang, Wenzhao Zheng +5

Video diffusion models, trained on large-scale datasets, naturally capture correspondences of shared features across frames. Recent works have exploited this property for tasks suc…

cs.CV2025

Terra: Explorable Native 3D World Model with Point Latents

Yuanhui Huang, Weiliang Chen, Wenzhao Zheng +4

World models have garnered increasing attention for comprehensive modeling of the real world. However, most existing methods still rely on pixel-aligned representations as the basi…

cs.CV2025

GenWorld: Towards Detecting AI-generated Real-world Simulation Videos

Weiliang Chen, Wenzhao Zheng, Yu Zheng +4

The flourishing of video generation technologies has endangered the credibility of real-world information and intensified the demand for AI-generated video detectors. Despite some…

cs.CV2025

SpectralAR: Spectral Autoregressive Visual Generation

Yuanhui Huang, Weiliang Chen, Wenzhao Zheng +3

Autoregressive visual generation has garnered increasing attention due to its scalability and compatibility with other modalities compared with diffusion models. Most existing meth…

cs.CV20235 cited

OccWorld: Learning a 3D Occupancy World Model for Autonomous Driving

Wenzhao Zheng, Weiliang Chen, Yuanhui Huang +3

Understanding how the 3D scene evolves is vital for making decisions in autonomous driving. Most existing methods achieve this by predicting the movements of object boxes, which ca…