Choose your simulator wisely: A review on open-source simulators for autonomous driving

Y Li, W Yuan, S Zhang, W Yan, Q Shen… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Simulators play a crucial role in autonomous driving, offering significant time, cost, and labor
savings. Over the past few years, the number of simulators for autonomous driving has …

Xcube: Large-scale 3d generative modeling using sparse voxel hierarchies

X Ren, J Huang, X Zeng, K Museth… - Proceedings of the …, 2024 - openaccess.thecvf.com
We present XCube a novel generative model for high-resolution sparse 3D voxel grids with
arbitrary attributes. Our model can generate millions of voxels with a finest effective …

4k4dgen: Panoramic 4d generation at 4k resolution

R Li, P Pan, B Yang, D Xu, S Zhou, X Zhang… - ar**
J Zhou, B Ma, YS Liu - IEEE transactions on pattern analysis …, 2024 - ieeexplore.ieee.org
Learning signed distance functions (SDFs) from point clouds is an important task in 3D
computer vision. However, without ground truth signed distances, point normals or clean …

Unsupervised occupancy learning from sparse point cloud

A Ouasfi, A Boukhayma - … of the IEEE/CVF Conference on …, 2024 - openaccess.thecvf.com
Abstract Implicit Neural Representations have gained prominence as a powerful framework
for capturing complex data modalities encompassing a wide range from 3D shapes to …

Pin-slam: Lidar slam using a point-based implicit neural representation for achieving global map consistency

Y Pan, X Zhong, L Wiesmann, T Posewsky… - ar** are essential components for most
autonomous robots. In this paper, we propose a SLAM system for building globally …

Few-shot unsupervised implicit neural shape representation learning with spatial adversaries

A Ouasfi, A Boukhayma - arxiv preprint arxiv:2408.15114, 2024 - arxiv.org
Implicit Neural Representations have gained prominence as a powerful framework for
capturing complex data modalities, encompassing a wide range from 3D shapes to images …

Implicit filtering for learning neural signed distance functions from 3d point clouds

S Li, G Gao, Y Liu, M Gu, YS Liu - European Conference on Computer …, 2024 - Springer
Neural signed distance functions (SDFs) have shown powerful ability in fitting the shape
geometry. However, inferring continuous signed distance fields from discrete unoriented …