Search Results for author: Jiahui Huang

Found 12 papers, 5 papers with code

Multiway Non-rigid Point Cloud Registration via Learned Functional Map Synchronization

no code implementations25 Nov 2021 Jiahui Huang, Tolga Birdal, Zan Gojcic, Leonidas J. Guibas, Shi-Min Hu

We present SyNoRiM, a novel way to jointly register multiple non-rigid shapes by synchronizing the maps relating learned functions defined on the point clouds.

Point Cloud Registration

CIRCLE: Convolutional Implicit Reconstruction and Completion for Large-scale Indoor Scene

no code implementations25 Nov 2021 Haoxiang Chen, Jiahui Huang, Tai-Jiang Mu, Shi-Min Hu

We present CIRCLE, a framework for large-scale scene completion and geometric refinement based on local implicit signed distance functions.

Layered Controllable Video Generation

no code implementations24 Nov 2021 Jiahui Huang, Yuhe Jin, Kwang Moo Yi, Leonid Sigal

In the first stage, with the rich set of losses and dynamic foreground size prior, we learn how to separate the frame into foreground and background layers and, conditioned on these layers, how to generate the next frame using VQ-VAE generator.

Video Generation

Subdivision-Based Mesh Convolution Networks

1 code implementation4 Jun 2021 Shi-Min Hu, Zheng-Ning Liu, Meng-Hao Guo, Jun-Xiong Cai, Jiahui Huang, Tai-Jiang Mu, Ralph R. Martin

Meshes with arbitrary connectivity can be remeshed to have Loop subdivision sequence connectivity via self-parameterization, making SubdivNet a general approach.

3D Classification

MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization

1 code implementation CVPR 2021 Jiahui Huang, He Wang, Tolga Birdal, Minhyuk Sung, Federica Arrigoni, Shi-Min Hu, Leonidas Guibas

We present MultiBodySync, a novel, end-to-end trainable multi-body motion segmentation and rigid registration framework for multiple input 3D point clouds.

Motion Estimation Motion Segmentation

DI-Fusion: Online Implicit 3D Reconstruction with Deep Priors

2 code implementations CVPR 2021 Jiahui Huang, Shi-Sheng Huang, Haoxuan Song, Shi-Min Hu

Previous online 3D dense reconstruction methods struggle to achieve the balance between memory storage and surface quality, largely due to the usage of stagnant underlying geometry representation, such as TSDF (truncated signed distance functions) or surfels, without any knowledge of the scene priors.

3D Reconstruction

Duality Diagram Similarity: a generic framework for initialization selection in task transfer learning

2 code implementations ECCV 2020 Kshitij Dwivedi, Jiahui Huang, Radoslaw Martin Cichy, Gemma Roig

In this paper, we tackle an open research question in transfer learning, which is selecting a model initialization to achieve high performance on a new task, given several pre-trained models.

Model Selection Semantic Segmentation +1

ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundings

no code implementations CVPR 2020 Jiahui Huang, Sheng Yang, Tai-Jiang Mu, Shi-Min Hu

We present ClusterVO, a stereo Visual Odometry which simultaneously clusters and estimates the motion of both ego and surrounding rigid clusters/objects.

Autonomous Driving Scene Understanding +1

Shallow2Deep: Indoor Scene Modeling by Single Image Understanding

no code implementations22 Feb 2020 Yinyu Nie, Shihui Guo, Jian Chang, Xiaoguang Han, Jiahui Huang, Shi-Min Hu, Jian Jun Zhang

Particularly, we design a shallow-to-deep architecture on the basis of convolutional networks for semantic scene understanding and modeling.

Scene Understanding

ClusterSLAM: A SLAM Backend for Simultaneous Rigid Body Clustering and Motion Estimation

no code implementations ICCV 2019 Jiahui Huang, Sheng Yang, Zishuo Zhao, Yu-Kun Lai, Shi-Min Hu

We present a practical backend for stereo visual SLAM which can simultaneously discover individual rigid bodies and compute their motions in dynamic environments.

Motion Estimation

Deep Anchored Convolutional Neural Networks

no code implementations22 Apr 2019 Jiahui Huang, Kshitij Dwivedi, Gemma Roig

Convolutional Neural Networks (CNNs) have been proven to be extremely successful at solving computer vision tasks.

DeepSpline: Data-Driven Reconstruction of Parametric Curves and Surfaces

2 code implementations12 Jan 2019 Jun Gao, Chengcheng Tang, Vignesh Ganapathi-Subramanian, Jiahui Huang, Hao Su, Leonidas J. Guibas

Reconstruction of geometry based on different input modes, such as images or point clouds, has been instrumental in the development of computer aided design and computer graphics.

Cannot find the paper you are looking for? You can Submit a new open access paper.