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20232026
most citedIs Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond

8 citations · 19 across the 17 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CV2024

OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation

Bohan Li, Xin Jin, Jianan Wang +8

Recent diffusion models have demonstrated remarkable performance in both 3D scene generation and perception tasks. Nevertheless, existing methods typically separate these two proce…

cs.CV2024

Hierarchical Context Alignment with Disentangled Geometric and Temporal Modeling for Semantic Occupancy Prediction

Bohan Li, Jiajun Deng, Yasheng Sun +3

Camera-based 3D Semantic Occupancy Prediction (SOP) is crucial for understanding complex 3D scenes from limited 2D image observations. Existing SOP methods typically aggregate cont…

cs.CV2024

Hierarchical Temporal Context Learning for Camera-based Semantic Scene Completion

Bohan Li, Jiajun Deng, Wenyao Zhang +4

Camera-based 3D semantic scene completion (SSC) is pivotal for predicting complicated 3D layouts with limited 2D image observations. The existing mainstream solutions generally lev…

cs.CV2024★ 8 cited

Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond

Zheng Zhu, Xiaofeng Wang, Wangbo Zhao +15

General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual en…

cs.CV2024★ 1 cited

Closed-Loop Unsupervised Representation Disentanglement with -VAE Distillation and Diffusion Probabilistic Feedback

Xin Jin, Bohan Li, BAAO Xie +5

Representation disentanglement may help AI fundamentally understand the real world and thus benefit both discrimination and generation tasks. It currently has at least three unreso…