46 citations · 147 across the 13 of their papers we have counts for
14 papers
3DRM:Pair-wise relation module for 3D object detection
Yuqing Lan, Yao Duan, Yifei Shi +2
Context has proven to be one of the most important factors in object layout reasoning for 3D scene understanding. Existing deep contextual models either learn holistic features for…
Learning Practically Feasible Policies for Online 3D Bin Packing
Hang Zhao, Chenyang Zhu, Xin Xu +2
We tackle the Online 3D Bin Packing Problem, a challenging yet practically useful variant of the classical Bin Packing Problem. In this problem, the items are delivered to the agen…
Consistent Two-Flow Network for Tele-Registration of Point Clouds
Zihao Yan, Zimu Yi, Ruizhen Hu +3
Rigid registration of partial observations is a fundamental problem in various applied fields. In computer graphics, special attention has been given to the registration between tw…
RPG: Learning Recursive Point Cloud Generation
Wei-Jan Ko, Hui-Yu Huang, Yu-Liang Kuo +3
In this paper we propose a novel point cloud generator that is able to reconstruct and generate 3D point clouds composed of semantic parts. Given a latent representation of the tar…
VGF-Net: Visual-Geometric Fusion Learning for Simultaneous Drone Navigation and Height Mapping
Yilin Liu, Ke Xie, Hui Huang
The drone navigation requires the comprehensive understanding of both visual and geometric information in the 3D world. In this paper, we present a Visual-Geometric Fusion Network(…
Shape-driven Coordinate Ordering for Star Glyph Sets via Reinforcement Learning
Ruizhen Hu, Bin Chen, Juzhan Xu +3
We present a neural optimization model trained with reinforcement learning to solve the coordinate ordering problem for sets of star glyphs. Given a set of star glyphs associated t…
Hausdorff Point Convolution with Geometric Priors
Pengdi Huang, Liqiang Lin, Fuyou Xue +3
Without a shape-aware response, it is hard to characterize the 3D geometry of a point cloud efficiently with a compact set of kernels. In this paper, we advocate the use of Hausdor…
Autonomous Outdoor Scanning via Online Topological and Geometric Path Optimization
Pengdi Huang, Liqiang Lin, Kai Xu +1
Autonomous 3D acquisition of outdoor environments poses special challenges. Different from indoor scenes, where the room space is delineated by clear boundaries and separations (e.…
TAP-Net: Transport-and-Pack using Reinforcement Learning
Ruizhen Hu, Juzhan Xu, Bin Chen +3
We introduce the transport-and-pack(TAP) problem, a frequently encountered instance of real-world packing, and develop a neural optimization solution based on reinforcement learnin…
Predictive and Generative Neural Networks for Object Functionality
Ruizhen Hu, Zihao Yan, Jingwen Zhang +4
Humans can predict the functionality of an object even without any surroundings, since their knowledge and experience would allow them to "hallucinate" the interaction or usage sce…
ETNet: Error Transition Network for Arbitrary Style Transfer
Chunjin Song, Zhijie Wu, Yang Zhou +2
Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the seminal work of Gatys et al. However, existing state-of-the-art approaches often generat…
Active Scene Understanding via Online Semantic Reconstruction
Lintao Zheng, Chenyang Zhu, Jiazhao Zhang +4
We propose a novel approach to robot-operated active understanding of unknown indoor scenes, based on online RGBD reconstruction with semantic segmentation. In our method, the expl…
Object-Aware Guidance for Autonomous Scene Reconstruction
Ligang Liu, Xi Xia, Han Sun +5
To carry out autonomous 3D scanning and online reconstruction of unknown indoor scenes, one has to find a balance between global exploration of the entire scene and local scanning…
Full 3D Reconstruction of Transparent Objects
Bojian Wu, Yang Zhou, Yiming Qian +2
Numerous techniques have been proposed for reconstructing 3D models for opaque objects in past decades. However, none of them can be directly applied to transparent objects. This p…