321 citations · 555 across the 36 of their papers we have counts for
39 papers
HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Driving
Hongyu Zhou, Longzhong Lin, Jiabao Wang +6
In the past few decades, autonomous driving algorithms have made significant progress in perception, planning, and control. However, evaluating individual components does not fully…
Efficient Depth-Guided Urban View Synthesis
Sheng Miao, Jiaxin Huang, Dongfeng Bai +4
Recent advances in implicit scene representation enable high-fidelity street view novel view synthesis. However, existing methods optimize a neural radiance field for each scene, r…
PanopticRecon: Leverage Open-vocabulary Instance Segmentation for Zero-shot Panoptic Reconstruction
Xuan Yu, Yili Liu, Chenrui Han +5
Panoptic reconstruction is a challenging task in 3D scene understanding. However, most existing methods heavily rely on pre-trained semantic segmentation models and known 3D object…
Learning Temporally Consistent Video Depth from Video Diffusion Priors
Jiahao Shao, Yuanbo Yang, Hongyu Zhou +6
This work addresses the challenge of streamed video depth estimation, which expects not only per-frame accuracy but, more importantly, cross-frame consistency. We argue that sharin…
NeRFCodec: Neural Feature Compression Meets Neural Radiance Fields for Memory-Efficient Scene Representation
Sicheng Li, Hao Li, Yiyi Liao +1
The emergence of Neural Radiance Fields (NeRF) has greatly impacted 3D scene modeling and novel-view synthesis. As a kind of visual media for 3D scene representation, compression w…
Learning 3D-Aware GANs from Unposed Images with Template Feature Field
Xinya Chen, Hanlei Guo, Yanrui Bin +5
Collecting accurate camera poses of training images has been shown to well serve the learning of 3D-aware generative adversarial networks (GANs) yet can be quite expensive in pract…
HUGS: Holistic Urban 3D Scene Understanding via Gaussian Splatting
Hongyu Zhou, Jiahao Shao, Lu Xu +6
Holistic understanding of urban scenes based on RGB images is a challenging yet important problem. It encompasses understanding both the geometry and appearance to enable novel vie…
REFRAME: Reflective Surface Real-Time Rendering for Mobile Devices
Chaojie Ji, Yufeng Li, Yiyi Liao
This work tackles the challenging task of achieving real-time novel view synthesis for reflective surfaces across various scenes. Existing real-time rendering methods, especially t…
Recent Trends in 3D Reconstruction of General Non-Rigid Scenes
Raza Yunus, Jan Eric Lenssen, Michael Niemeyer +7
Reconstructing models of the real world, including 3D geometry, appearance, and motion of real scenes, is essential for computer graphics and computer vision. It enables the synthe…
Reality3DSketch: Rapid 3D Modeling of Objects from Single Freehand Sketches
Tianrun Chen, Chaotao Ding, Lanyun Zhu +4
The emerging trend of AR/VR places great demands on 3D content. However, most existing software requires expertise and is difficult for novice users to use. In this paper, we aim t…
DORec: Decomposed Object Reconstruction and Segmentation Utilizing 2D Self-Supervised Features
Jun Wu, Sicheng Li, Sihui Ji +4
Recovering 3D geometry and textures of individual objects is crucial for many robotics applications, such as manipulation, pose estimation, and autonomous driving. However, decompo…
VeRi3D: Generative Vertex-based Radiance Fields for 3D Controllable Human Image Synthesis
Xinya Chen, Jiaxin Huang, Yanrui Bin +2
Unsupervised learning of 3D-aware generative adversarial networks has lately made much progress. Some recent work demonstrates promising results of learning human generative models…
PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes
Xiao Fu, Shangzhan Zhang, Tianrun Chen +4
Training perception systems for self-driving cars requires substantial 2D annotations that are labor-intensive to manual label. While existing datasets provide rich annotations on…
MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Driving
Zirui Wu, Tianyu Liu, Liyi Luo +13
Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner c…
NF-Atlas: Multi-Volume Neural Feature Fields for Large Scale LiDAR Mapping
Xuan Yu, Yili Liu, Sitong Mao +4
LiDAR Mapping has been a long-standing problem in robotics. Recent progress in neural implicit representation has brought new opportunities to robotic mapping. In this paper, we pr…
UrbanGIRAFFE: Representing Urban Scenes as Compositional Generative Neural Feature Fields
Yuanbo Yang, Yifei Yang, Hanlei Guo +3
Generating photorealistic images with controllable camera pose and scene contents is essential for many applications including AR/VR and simulation. Despite the fact that rapid pro…
RICO: Regularizing the Unobservable for Indoor Compositional Reconstruction
Zizhang Li, Xiaoyang Lyu, Yuanyuan Ding +3
Recently, neural implicit surfaces have become popular for multi-view reconstruction. To facilitate practical applications like scene editing and manipulation, some works extend th…
Painting 3D Nature in 2D: View Synthesis of Natural Scenes from a Single Semantic Mask
Shangzan Zhang, Sida Peng, Tianrun Chen +5
We introduce a novel approach that takes a single semantic mask as input to synthesize multi-view consistent color images of natural scenes, trained with a collection of single ima…
Learning 3D-aware Image Synthesis with Unknown Pose Distribution
Zifan Shi, Yujun Shen, Yinghao Xu +5
Existing methods for 3D-aware image synthesis largely depend on the 3D pose distribution pre-estimated on the training set. An inaccurate estimation may mislead the model into lear…
SteerNeRF: Accelerating NeRF Rendering via Smooth Viewpoint Trajectory
Sicheng Li, Hao Li, Yue Wang +2
Neural Radiance Fields (NeRF) have demonstrated superior novel view synthesis performance but are slow at rendering. To speed up the volume rendering process, many acceleration met…
RING++: Roto-translation Invariant Gram for Global Localization on a Sparse Scan Map
Xuecheng Xu, Sha Lu, Jun Wu +5
Global localization plays a critical role in many robot applications. LiDAR-based global localization draws the community's focus with its robustness against illumination and seaso…
Deep Generative Models on 3D Representations: A Survey
Zifan Shi, Sida Peng, Yinghao Xu +3
Generative models aim to learn the distribution of observed data by generating new instances. With the advent of neural networks, deep generative models, including variational auto…
DPCN++: Differentiable Phase Correlation Network for Versatile Pose Registration
Zexi Chen, Yiyi Liao, Haozhe Du +5
Pose registration is critical in vision and robotics. This paper focuses on the challenging task of initialization-free pose registration up to 7DoF for homogeneous and heterogeneo…
VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Grids
Katja Schwarz, Axel Sauer, Michael Niemeyer +2
State-of-the-art 3D-aware generative models rely on coordinate-based MLPs to parameterize 3D radiance fields. While demonstrating impressive results, querying an MLP for every samp…