134 citations · 277 across the 12 of their papers we have counts for
12 papers · 1 filter
Sharp Monocular View Synthesis in Less Than a Second
Lars Mescheder, Wei Dong, Shiwei Li +10
We present SHARP, an approach to photorealistic view synthesis from a single image. Given a single photograph, SHARP regresses the parameters of a 3D Gaussian representation of the…
Affine-based Deformable Attention and Selective Fusion for Semi-dense Matching
Hongkai Chen, Zixin Luo, Yurun Tian +8
Identifying robust and accurate correspondences across images is a fundamental problem in computer vision that enables various downstream tasks. Recent semi-dense matching methods…
One Training for Multiple Deployments: Polar-based Adaptive BEV Perception for Autonomous Driving
Huitong Yang, Xuyang Bai, Xinge Zhu +1
Current on-board chips usually have different computing power, which means multiple training processes are needed for adapting the same learning-based algorithm to different chips,…
LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation
Zeyu Hu, Xuyang Bai, Runze Zhang +4
We propose LiDAL, a novel active learning method for 3D LiDAR semantic segmentation by exploiting inter-frame uncertainty among LiDAR frames. Our core idea is that a well-trained m…
Vision-Centric BEV Perception: A Survey
Yuexin Ma, Tai Wang, Xuyang Bai +7
In recent years, vision-centric Bird's Eye View (BEV) perception has garnered significant interest from both industry and academia due to its inherent advantages, such as providing…
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers
Xuyang Bai, Zeyu Hu, Xinge Zhu +4
LiDAR and camera are two important sensors for 3D object detection in autonomous driving. Despite the increasing popularity of sensor fusion in this field, the robustness against i…
Learning to Match Features with Seeded Graph Matching Network
Hongkai Chen, Zixin Luo, Jiahui Zhang +5
Matching local features across images is a fundamental problem in computer vision. Targeting towards high accuracy and efficiency, we propose Seeded Graph Matching Network, a graph…
VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation
Zeyu Hu, Xuyang Bai, Jiaxiang Shang +6
In recent years, sparse voxel-based methods have become the state-of-the-arts for 3D semantic segmentation of indoor scenes, thanks to the powerful 3D CNNs. Nevertheless, being obl…
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency
Xuyang Bai, Zixin Luo, Lei Zhou +5
Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration. Despite the increasing popularity of introducing deep learning…
JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds
Zeyu Hu, Mingmin Zhen, Xuyang Bai +2
Semantic segmentation and semantic edge detection can be seen as two dual problems with close relationships in computer vision. Despite the fast evolution of learning-based 3D sema…
ASLFeat: Learning Local Features of Accurate Shape and Localization
Zixin Luo, Lei Zhou, Xuyang Bai +6
This work focuses on mitigating two limitations in the joint learning of local feature detectors and descriptors. First, the ability to estimate the local shape (scale, orientation…
D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features
Xuyang Bai, Zixin Luo, Lei Zhou +3
A successful point cloud registration often lies on robust establishment of sparse matches through discriminative 3D local features. Despite the fast evolution of learning-based 3D…