Search Results for author: Lei Bai

Found 11 papers, 4 papers with code

Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images

no code implementations13 Sep 2021 Size Wu, Sheng Jin, Wentao Liu, Lei Bai, Chen Qian, Dong Liu, Wanli Ouyang

Following the top-down paradigm, we decompose the task into two stages, i. e. person localization and pose estimation.

3D Multi-Person Pose Estimation 3D Pose Estimation +1

PSViT: Better Vision Transformer via Token Pooling and Attention Sharing

no code implementations7 Aug 2021 BoYu Chen, Peixia Li, Baopu Li, Chuming Li, Lei Bai, Chen Lin, Ming Sun, Junjie Yan, Wanli Ouyang

Then, a compact set of the possible combinations for different token pooling and attention sharing mechanisms are constructed.

Mutual CRF-GNN for Few-Shot Learning

no code implementations CVPR 2021 Shixiang Tang, Dapeng Chen, Lei Bai, Kaijian Liu, Yixiao Ge, Wanli Ouyang

In this MCGN, the labels and features of support data are used by the CRF for inferring GNN affinities in a principled and probabilistic way.

Few-Shot Learning

Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving

no code implementations27 Nov 2020 Zhenxun Yuan, Xiao Song, Lei Bai, Wengang Zhou, Zhe Wang, Wanli Ouyang

As a special design of this transformer, the information encoded in the encoder is different from that in the decoder, i. e. the encoder encodes temporal-channel information of multiple frames while the decoder decodes the spatial-channel information for the current frame in a voxel-wise manner.

3D Object Detection Autonomous Driving +1

Knowledge Adaption for Demand Prediction based on Multi-task Memory Neural Network

no code implementations12 Sep 2020 Can Li, Lei Bai, Wei Liu, Lina Yao, S Travis Waller

Accurate demand forecasting of different public transport modes(e. g., buses and light rails) is essential for public service operation. However, the development level of various modes often varies sig-nificantly, which makes it hard to predict the demand of the modeswith insufficient knowledge and sparse station distribution (i. e., station-sparse mode).

Multi-Task Learning

Spectrum-Guided Adversarial Disparity Learning

1 code implementation14 Jul 2020 Zhe Liu, Lina Yao, Lei Bai, Xianzhi Wang, Can Wang

It has been a significant challenge to portray intraclass disparity precisely in the area of activity recognition, as it requires a robust representation of the correlation between subject-specific variation for each activity class.

Activity Recognition Denoising

Face to Purchase: Predicting Consumer Choices with Structured Facial and Behavioral Traits Embedding

no code implementations14 Jul 2020 Zhe Liu, Xianzhi Wang, Lina Yao, Jake An, Lei Bai, Ee-Peng Lim

We design a semi-supervised model based on a hierarchical embedding network to extract high-level features of consumers and to predict the top-$N$ purchase destinations of a consumer.

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

3 code implementations NeurIPS 2020 Lei Bai, Lina Yao, Can Li, Xianzhi Wang, Can Wang

We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.

Graph Generation Multivariate Time Series Forecasting +4

Are You A Risk Taker? Adversarial Learning of Asymmetric Cross-Domain Alignment for Risk Tolerance Prediction

no code implementations18 Apr 2020 Zhe Liu, Lina Yao, Xianzhi Wang, Lei Bai, Jake An

Most current studies on survey analysis and risk tolerance modelling lack professional knowledge and domain-specific models.

Representation Learning

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