31 citations · 280 across the 41 of their papers we have counts for
11 papers · 1 filter
NICE-SLAM: Neural Implicit Scalable Encoding for SLAM
Zihan Zhu, Songyou Peng, Viktor Larsson +5
Neural implicit representations have recently shown encouraging results in various domains, including promising progress in simultaneous localization and mapping (SLAM). Neverthele…
LatentHuman: Shape-and-Pose Disentangled Latent Representation for Human Bodies
Sandro Lombardi, Bangbang Yang, Tianxing Fan +4
3D representation and reconstruction of human bodies have been studied for a long time in computer vision. Traditional methods rely mostly on parametric statistical linear models,…
Non-local Recurrent Regularization Networks for Multi-view Stereo
Qingshan Xu, Martin R. Oswald, Wenbing Tao +2
In deep multi-view stereo networks, cost regularization is crucial to achieve accurate depth estimation. Since 3D cost volume filtering is usually memory-consuming, recurrent 2D co…
Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering
Bangbang Yang, Yinda Zhang, Yinghao Xu +5
Implicit neural rendering techniques have shown promising results for novel view synthesis. However, existing methods usually encode the entire scene as a whole, which is generally…
DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based Optimization
Cheng Zhang, Zhaopeng Cui, Cai Chen +4
Panorama images have a much larger field-of-view thus naturally encode enriched scene context information compared to standard perspective images, which however is not well exploit…
Deep Hybrid Self-Prior for Full 3D Mesh Generation
Xingkui Wei, Zhengqing Chen, Yanwei Fu +2
We present a deep learning pipeline that leverages network self-prior to recover a full 3D model consisting of both a triangular mesh and a texture map from the colored 3D point cl…
Vis2Mesh: Efficient Mesh Reconstruction from Unstructured Point Clouds of Large Scenes with Learned Virtual View Visibility
Shuang Song, Zhaopeng Cui, Rongjun Qin
We present a novel framework for mesh reconstruction from unstructured point clouds by taking advantage of the learned visibility of the 3D points in the virtual views and traditio…
Towards Efficient Graph Convolutional Networks for Point Cloud Handling
Yawei Li, He Chen, Zhaopeng Cui +4
In this paper, we aim at improving the computational efficiency of graph convolutional networks (GCNs) for learning on point clouds. The basic graph convolution that is typically c…
Riggable 3D Face Reconstruction via In-Network Optimization
Ziqian Bai, Zhaopeng Cui, Xiaoming Liu +1
This paper presents a method for riggable 3D face reconstruction from monocular images, which jointly estimates a personalized face rig and per-image parameters including expressio…
Holistic 3D Scene Understanding from a Single Image with Implicit Representation
Cheng Zhang, Zhaopeng Cui, Yinda Zhang +3
We present a new pipeline for holistic 3D scene understanding from a single image, which could predict object shapes, object poses, and scene layout. As it is a highly ill-posed pr…
P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching
Bing Wang, Changhao Chen, Zhaopeng Cui +8
Accurately describing and detecting 2D and 3D keypoints is crucial to establishing correspondences across images and point clouds. Despite a plethora of learning-based 2D or 3D loc…