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20232026
most citedOccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments

7 citations · 20 across the 46 of their papers we have counts for

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Showing 2024 · cs.CVShow all

18 papers · 2 filters

cs.CV2024★ 1 cited

Preventing Local Pitfalls in Vector Quantization via Optimal Transport

Borui Zhang, Wenzhao Zheng, Jie Zhou +1

Vector-quantized networks (VQNs) have exhibited remarkable performance across various tasks, yet they are prone to training instability, which complicates the training process due…

cs.CV2024

GaussianWorld: Gaussian World Model for Streaming 3D Occupancy Prediction

Sicheng Zuo, Wenzhao Zheng, Yuanhui Huang +2

3D occupancy prediction is important for autonomous driving due to its comprehensive perception of the surroundings. To incorporate sequential inputs, most existing methods fuse re…

cs.CV2024

Doe-1: Closed-Loop Autonomous Driving with Large World Model

Wenzhao Zheng, Zetian Xia, Yuanhui Huang +3

End-to-end autonomous driving has received increasing attention due to its potential to learn from large amounts of data. However, most existing methods are still open-loop and suf…

cs.CV2024

Owl-1: Omni World Model for Consistent Long Video Generation

Yuanhui Huang, Wenzhao Zheng, Yuan Gao +5

Video generation models (VGMs) have received extensive attention recently and serve as promising candidates for general-purpose large vision models. While they can only generate sh…

cs.CV2024

GPD-1: Generative Pre-training for Driving

Zixun Xie, Sicheng Zuo, Wenzhao Zheng +5

Modeling the evolutions of driving scenarios is important for the evaluation and decision-making of autonomous driving systems. Most existing methods focus on one aspect of scene e…

cs.CV2024

Stag-1: Towards Realistic 4D Driving Simulation with Video Generation Model

Lening Wang, Wenzhao Zheng, Dalong Du +8

4D driving simulation is essential for developing realistic autonomous driving simulators. Despite advancements in existing methods for generating driving scenes, significant chall…