most citedTri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction

8 citations · 21 across the 3 of their papers we have counts for

collaborators

5 papers

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

GaussianFormer-2: Probabilistic Gaussian Superposition for Efficient 3D Occupancy Prediction

Yuanhui Huang, Amonnut Thammatadatrakoon, Wenzhao Zheng +3

3D semantic occupancy prediction is an important task for robust vision-centric autonomous driving, which predicts fine-grained geometry and semantics of the surrounding scene. Mos…

cs.CV20238 cited

PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction

Sicheng Zuo, Wenzhao Zheng, Yuanhui Huang +2

Semantic segmentation in autonomous driving has been undergoing an evolution from sparse point segmentation to dense voxel segmentation, where the objective is to predict the seman…

cs.CV20238 cited

Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction

Yuanhui Huang, Wenzhao Zheng, Yunpeng Zhang +2

Modern methods for vision-centric autonomous driving perception widely adopt the bird's-eye-view (BEV) representation to describe a 3D scene. Despite its better efficiency than vox…