Search Results for author: Jian Pu

Found 13 papers, 4 papers with code

SUPS: A Simulated Underground Parking Scenario Dataset for Autonomous Driving

1 code implementation25 Feb 2023 Jiawei Hou, Qi Chen, Yurong Cheng, Guang Chen, xiangyang xue, Taiping Zeng, Jian Pu

However, there is a lack of underground parking scenario datasets with multiple sensors and well-labeled images that support both SLAM tasks and perception tasks, such as semantic segmentation and parking slot detection.

3D Reconstruction Autonomous Driving +4

MVFusion: Multi-View 3D Object Detection with Semantic-aligned Radar and Camera Fusion

no code implementations21 Feb 2023 Zizhang Wu, Guilian Chen, Yuanzhu Gan, Lei Wang, Jian Pu

To achieve so, we inject the semantic alignment into the radar features via the semantic-aligned radar encoder (SARE) to produce image-guided radar features.

3D Object Detection Autonomous Driving +1

SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP

1 code implementation18 Oct 2022 Jie Chen, Shouzhen Chen, Mingyuan Bai, Junbin Gao, Junping Zhang, Jian Pu

Then, we introduce a novel structure-mixing knowledge distillation strategy to enhance the learning ability of MLPs for structure information.

Knowledge Distillation Node Classification

Exploiting Neighbor Effect: Conv-Agnostic GNNs Framework for Graphs with Heterophily

no code implementations19 Mar 2022 Jie Chen, Shouzhen Chen, Junbin Gao, Zengfeng Huang, Junping Zhang, Jian Pu

Moreover, we propose a Conv-Agnostic GNNs framework (CAGNNs) to enhance the performance of GNNs on heterophily datasets by learning the neighbor effect for each node.

Node Classification

Memory-based Message Passing: Decoupling the Message for Propogation from Discrimination

1 code implementation1 Feb 2022 Jie Chen, Weiqi Liu, Jian Pu

Based on the homophily assumption, the current message passing always aggregates features of connected nodes, such as the graph Laplacian smoothing process.

Graph Representation Learning

Graph Decoupling Attention Markov Networks for Semi-supervised Graph Node Classification

no code implementations28 Apr 2021 Jie Chen, Shouzhen Chen, Mingyuan Bai, Jian Pu, Junping Zhang, Junbin Gao

In this paper, we consider the label dependency of graph nodes and propose a decoupling attention mechanism to learn both hard and soft attention.

General Classification Graph Learning +2

SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition

1 code implementation27 Mar 2021 Yiqun Liu, Yi Zeng, Jian Pu, Hongming Shan, Peiyang He, Junping Zhang

In this work, we propose a self-supervised gait recognition method, termed SelfGait, which takes advantage of the massive, diverse, unlabeled gait data as a pre-training process to improve the representation abilities of spatiotemporal backbones.

Gait Recognition Representation Learning

Crowd Counting with Density Adaption Networks

no code implementations26 Jun 2018 Li Wang, Weiyuan Shao, Yao Lu, Hao Ye, Jian Pu, Yingbin Zheng

Crowd counting is one of the core tasks in various surveillance applications.

Crowd Counting

tau-FPL: Tolerance-Constrained Learning in Linear Time

no code implementations15 Jan 2018 Ao Zhang, Nan Li, Jian Pu, Jun Wang, Junchi Yan, Hongyuan Zha

Learning a classifier with control on the false-positive rate plays a critical role in many machine learning applications.

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