Search Results for author: Manning Wang

Found 13 papers, 6 papers with code

POS-BERT: Point Cloud One-Stage BERT Pre-Training

1 code implementation3 Apr 2022 Kexue Fu, Peng Gao, Shaolei Liu, Renrui Zhang, Yu Qiao, Manning Wang

We propose to use the dynamically updated momentum encoder as the tokenizer, which is updated and outputs the dynamic supervision signal along with the training process.

Contrastive Learning Language Modelling +3

Distillation with Contrast is All You Need for Self-Supervised Point Cloud Representation Learning

no code implementations9 Feb 2022 Kexue Fu, Peng Gao, Renrui Zhang, Hongsheng Li, Yu Qiao, Manning Wang

Especially, we develop a variant of ViT for 3D point cloud feature extraction, which also achieves comparable results with existing backbones when combined with our framework, and visualization of the attention maps show that our model does understand the point cloud by combining the global shape information and multiple local structural information, which is consistent with the inspiration of our representation learning method.

Contrastive Learning Knowledge Distillation +1

TransFuse: A Unified Transformer-based Image Fusion Framework using Self-supervised Learning

no code implementations19 Jan 2022 Linhao Qu, Shaolei Liu, Manning Wang, Shiman Li, Siqi Yin, Qin Qiao, Zhijian Song

In order to encourage different fusion tasks to promote each other and increase the generalizability of the trained network, we integrate the three self-supervised auxiliary tasks by randomly choosing one of them to destroy a natural image in model training.

Multi-Exposure Image Fusion Self-Supervised Learning

TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework using Self-Supervised Multi-Task Learning

2 code implementations2 Dec 2021 Linhao Qu, Shaolei Liu, Manning Wang, Zhijian Song

In this paper, we propose TransMEF, a transformer-based multi-exposure image fusion framework that uses self-supervised multi-task learning.

Multi-Exposure Image Fusion Multi-Task Learning

A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds

no code implementations12 Apr 2021 Xiaoyuan Luo, Shaolei Liu, Kexue Fu, Manning Wang, Zhijian Song

In the UDA architecture, an encoder is shared between the networks for the self-supervised task and the main task of point cloud classification or segmentation, so that the encoder can be trained to extract features suitable for both the source and the target domain data.

Point Cloud Classification Self-Supervised Learning +1

WaveFuse: A Unified Deep Framework for Image Fusion with Discrete Wavelet Transform

1 code implementation28 Jul 2020 Shaolei Liu, Manning Wang, Zhijian Song

We propose an unsupervised image fusion architecture for multiple application scenarios based on the combination of multi-scale discrete wavelet transform through regional energy and deep learning.

A Novel Method for the Absolute Pose Problem with Pairwise Constraints

no code implementations25 Mar 2019 Yinlong Liu, Xuechen Li, Manning Wang, Guang Chen, Zhijian Song, Alois Knoll

In this paper, we consider pairwise constraints and propose a globally optimal algorithm for solving the absolute pose estimation problem.

Pose Estimation Translation

Fast and Globally Optimal Rigid Registration of 3D Point Sets by Transformation Decomposition

no code implementations29 Dec 2018 Xuechen Li, Yinlong Liu, Yiru Wang, Chen Wang, Manning Wang, Zhijian Song

However, the existing global methods are slow for two main reasons: the computational complexity of BnB is exponential to the problem dimensionality (which is six for 3D rigid registration), and the bound evaluation used in BnB is inefficient.


Organ at Risk Segmentation in Head and Neck CT Images by Using a Two-Stage Segmentation Framework Based on 3D U-Net

no code implementations25 Aug 2018 Yueyue Wang, Liang Zhao, Zhijian Song, Manning Wang

Accurate segmentation of organ at risk (OAR) play a critical role in the treatment planning of image guided radiation treatment of head and neck cancer.

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