10 citations · 11 across the 17 of their papers we have counts for
17 papers · 1 filter
LiAuto-GeoX: Efficient Grounded Driving Transformer
Jiawei Lian, Haoyi Sun, Yang Wu +8
Dense 3D reconstruction has demonstrated immense potential for spatial understanding, yet its viability as a real-time, onboard representation for autonomous driving remains an ope…
Geometry-to-Image Synthesis-Driven Generative Point Cloud Registration
Haobo Jiang, Jin Xie, Jian Yang +2
In this paper, we propose a novel 3D registration paradigm, Generative Point Cloud Registration, which bridges advanced 2D generative models with 3D matching tasks to enhance regis…
FUSER: Feed-Forward MUltiview 3D Registration Transformer and SE(3) Diffusion Refinement
Haobo Jiang, Jin Xie, Jian Yang +2
Registration of multiview point clouds conventionally relies on extensive pairwise matching to build a pose graph for global synchronization, which is computationally expensive and…
AD-GS: Object-Aware B-Spline Gaussian Splatting for Self-Supervised Autonomous Driving
Jiawei Xu, Kai Deng, Zexin Fan +3
Modeling and rendering dynamic urban driving scenes is crucial for self-driving simulation. Current high-quality methods typically rely on costly manual object tracklet annotations…
MaskHOI: Robust 3D Hand-Object Interaction Estimation via Masked Pre-training
Yuechen Xie, Haobo Jiang, Jian Yang +2
In 3D hand-object interaction (HOI) tasks, estimating precise joint poses of hands and objects from monocular RGB input remains highly challenging due to the inherent geometric amb…
VGGT-Long: Chunk it, Loop it, Align it -- Pushing VGGT's Limits on Kilometer-scale Long RGB Sequences
Kai Deng, Zexin Ti, Jiawei Xu +2
Foundation models for 3D vision have recently demonstrated remarkable capabilities in 3D perception. However, extending these models to large-scale RGB stream 3D reconstruction rem…
VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction
Ziyue Zhu, Shenlong Wang, Jin Xie +3
Recent advancements in camera-based occupancy prediction have focused on the simultaneous prediction of 3D semantics and scene flow, a task that presents significant challenges due…
Sketchy Bounding-box Supervision for 3D Instance Segmentation
Qian Deng, Le Hui, Jin Xie +1
Bounding box supervision has gained considerable attention in weakly supervised 3D instance segmentation. While this approach alleviates the need for extensive point-level annotati…
WeatherGen: A Unified Diverse Weather Generator for LiDAR Point Clouds via Spider Mamba Diffusion
Yang Wu, Yun Zhu, Kaihua Zhang +3
3D scene perception demands a large amount of adverse-weather LiDAR data, yet the cost of LiDAR data collection presents a significant scaling-up challenge. To this end, a series o…
SVG-IR: Spatially-Varying Gaussian Splatting for Inverse Rendering
Hanxiao Sun, YuPeng Gao, Jin Xie +2
Reconstructing 3D assets from images, known as inverse rendering (IR), remains a challenging task due to its ill-posed nature. 3D Gaussian Splatting (3DGS) has demonstrated impress…
Learning Class Prototypes for Unified Sparse Supervised 3D Object Detection
Yun Zhu, Le Hui, Hang Yang +3
Both indoor and outdoor scene perceptions are essential for embodied intelligence. However, current sparse supervised 3D object detection methods focus solely on outdoor scenes wit…
FastPCI: Motion-Structure Guided Fast Point Cloud Frame Interpolation
Tianyu Zhang, Guocheng Qian, Jin Xie +1
Point cloud frame interpolation is a challenging task that involves accurate scene flow estimation across frames and maintaining the geometry structure. Prevailing techniques often…
Grid4D: 4D Decomposed Hash Encoding for High-Fidelity Dynamic Gaussian Splatting
Jiawei Xu, Zexin Fan, Jian Yang +1
Recently, Gaussian splatting has received more and more attention in the field of static scene rendering. Due to the low computational overhead and inherent flexibility of explicit…
Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformer
Yang Wu, Kaihua Zhang, Jianjun Qian +2
The complex traffic environment and various weather conditions make the collection of LiDAR data expensive and challenging. Achieving high-quality and controllable LiDAR data gener…
SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation
Haobo Jiang, Mathieu Salzmann, Zheng Dang +2
In this paper, we introduce an SE(3) diffusion model-based point cloud registration framework for 6D object pose estimation in real-world scenarios. Our approach formulates the 3D…
SGNet: Salient Geometric Network for Point Cloud Registration
Qianliang Wu, Yaqing Ding, Lei Luo +5
Point Cloud Registration (PCR) is a critical and challenging task in computer vision. One of the primary difficulties in PCR is identifying salient and meaningful points that exhib…
Point Cloud Registration-Driven Robust Feature Matching for 3D Siamese Object Tracking
Haobo Jiang, Kaihao Lan, Le Hui +3
Learning robust feature matching between the template and search area is crucial for 3D Siamese tracking. The core of Siamese feature matching is how to assign high feature similar…