Search Results for author: Tai-Jiang Mu

Found 13 papers, 6 papers with code

Long Range Pooling for 3D Large-Scale Scene Understanding

no code implementations CVPR 2023 Xiang-Li Li, Meng-Hao Guo, Tai-Jiang Mu, Ralph R. Martin, Shi-Min Hu

To achieve the above properties, we propose a simple yet effective long range pooling (LRP) module using dilation max pooling, which provides a network with a large adaptive receptive field.

Scene Understanding

MonoNeuralFusion: Online Monocular Neural 3D Reconstruction with Geometric Priors

no code implementations30 Sep 2022 Zi-Xin Zou, Shi-Sheng Huang, Yan-Pei Cao, Tai-Jiang Mu, Ying Shan, Hongbo Fu

This paper introduces a novel neural implicit scene representation with volume rendering for high-fidelity online 3D scene reconstruction from monocular videos.

3D Reconstruction 3D Scene Reconstruction

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.

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

Can Attention Enable MLPs To Catch Up With CNNs?

no code implementations31 May 2021 Meng-Hao Guo, Zheng-Ning Liu, Tai-Jiang Mu, Dun Liang, Ralph R. Martin, Shi-Min Hu

In the first week of May, 2021, researchers from four different institutions: Google, Tsinghua University, Oxford University and Facebook, shared their latest work [16, 7, 12, 17] on arXiv. org almost at the same time, each proposing new learning architectures, consisting mainly of linear layers, claiming them to be comparable, or even superior to convolutional-based models.

Recursive-NeRF: An Efficient and Dynamically Growing NeRF

1 code implementation19 May 2021 Guo-Wei Yang, Wen-Yang Zhou, Hao-Yang Peng, Dun Liang, Tai-Jiang Mu, Shi-Min Hu

Only query coordinates with high uncertainties are forwarded to the next level to a bigger neural network with a more powerful representational capability.

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks

7 code implementations5 May 2021 Meng-Hao Guo, Zheng-Ning Liu, Tai-Jiang Mu, Shi-Min Hu

Attention mechanisms, especially self-attention, have played an increasingly important role in deep feature representation for visual tasks.

Image Classification Image Generation +5

PCT: Point cloud transformer

9 code implementations17 Dec 2020 Meng-Hao Guo, Jun-Xiong Cai, Zheng-Ning Liu, Tai-Jiang Mu, Ralph R. Martin, Shi-Min Hu

It is inherently permutation invariant for processing a sequence of points, making it well-suited for point cloud learning.

3D Part Segmentation 3D Point Cloud Classification +1

Alternating ConvLSTM: Learning Force Propagation with Alternate State Updates

no code implementations14 Jun 2020 Congyue Deng, Tai-Jiang Mu, Shi-Min Hu

Experimental results show that Alt-ConvLSTM efficiently models the material kinetic features and greatly outperforms vanilla ConvLSTM with only the single state update.

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 Clustering +2

S4Net: Single Stage Salient-Instance Segmentation

1 code implementation CVPR 2019 Ruochen Fan, Ming-Ming Cheng, Qibin Hou, Tai-Jiang Mu, Jingdong Wang, Shi-Min Hu

Taking into account the category-independent property of each target, we design a single stage salient instance segmentation framework, with a novel segmentation branch.

Instance Segmentation Semantic Segmentation

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