15 citations · 15 across the 5 of their papers we have counts for
7 papers
OnePose: One-Shot Object Pose Estimation without CAD Models
Jiaming Sun, Zihao Wang, Siyu Zhang +4
We propose a new method named OnePose for object pose estimation. Unlike existing instance-level or category-level methods, OnePose does not rely on CAD models and can handle objec…
High-fidelity 3D Model Compression based on Key Spheres
Yuanzhan Li, Yuqi Liu, Yujie Lu +3
In recent years, neural signed distance function (SDF) has become one of the most effective representation methods for 3D models. By learning continuous SDFs in 3D space, neural ne…
SN-Graph: a Minimalist 3D Object Representation for Classification
Siyu Zhang, Hui Cao, Yuqi Liu +4
Using deep learning techniques to process 3D objects has achieved many successes. However, few methods focus on the representation of 3D objects, which could be more effective for…
Unsupervised Deep Representation Learning and Few-Shot Classification of PolSAR Images
Lamei Zhang, Siyu Zhang, Bin Zou +1
Deep learning and convolutional neural networks (CNNs) have made progress in polarimetric synthetic aperture radar (PolSAR) image classification over the past few years. However, a…
Disp R-CNN: Stereo 3D Object Detection via Shape Prior Guided Instance Disparity Estimation
Jiaming Sun, Linghao Chen, Yiming Xie +4
In this paper, we propose a novel system named Disp R-CNN for 3D object detection from stereo images. Many recent works solve this problem by first recovering a point cloud with di…
InSphereNet: a Concise Representation and Classification Method for 3D Object
Hui Cao, Haikuan Du, Siyu Zhang +1
In this paper, we present an InSphereNet method for the problem of 3D object classification. Unlike previous methods that use points, voxels, or multi-view images as inputs of deep…