Search Results for author: Zhipeng Luo

Found 37 papers, 11 papers with code

AMLN: Adversarial-based Mutual Learning Network for Online Knowledge Distillation

no code implementations ECCV 2020 Xiaobing Zhang, Shijian Lu, Haigang Gong, Zhipeng Luo, Ming Liu

Online knowledge distillation has attracted increasing interest recently, which jointly learns teacher and student models or an ensemble of student models simultaneously and collaboratively.

Knowledge Distillation Transfer Learning

DeepBlueAI at WANLP-EACL2021 task 2: A Deep Ensemble-based Method for Sarcasm and Sentiment Detection in Arabic

no code implementations EACL (WANLP) 2021 Bingyan Song, Chunguang Pan, Shengguang Wang, Zhipeng Luo

Sarcasm is one of the main challenges for sentiment analysis systems due to using implicit indirect phrasing for expressing opinions, especially in Arabic.

Sentiment Analysis Task 2

A Survey of Route Recommendations: Methods, Applications, and Opportunities

no code implementations1 Mar 2024 Shiming Zhang, Zhipeng Luo, Li Yang, Fei Teng, Tianrui Li

Our survey offers a comprehensive review of route recommendation work based on urban computing.

Modeling Continuous Motion for 3D Point Cloud Object Tracking

no code implementations14 Mar 2023 Zhipeng Luo, Gongjie Zhang, Changqing Zhou, Zhonghua Wu, Qingyi Tao, Lewei Lu, Shijian Lu

The task of 3D single object tracking (SOT) with LiDAR point clouds is crucial for various applications, such as autonomous driving and robotics.

3D Single Object Tracking Autonomous Driving +2

Towards Efficient Use of Multi-Scale Features in Transformer-Based Object Detectors

no code implementations CVPR 2023 Gongjie Zhang, Zhipeng Luo, Zichen Tian, Jingyi Zhang, Xiaoqin Zhang, Shijian Lu

Multi-scale features have been proven highly effective for object detection but often come with huge and even prohibitive extra computation costs, especially for the recent Transformer-based detectors.

Object object-detection +1

Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer

1 code implementation10 Aug 2022 Zhipeng Luo, Changqing Zhou, Liang Pan, Gongjie Zhang, Tianrui Liu, Yueru Luo, Haiyu Zhao, Ziwei Liu, Shijian Lu

In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in consecutive frames given an object template.

3D Object Tracking Autonomous Driving +3

TransPillars: Coarse-to-Fine Aggregation for Multi-Frame 3D Object Detection

no code implementations4 Aug 2022 Zhipeng Luo, Gongjie Zhang, Changqing Zhou, Tianrui Liu, Shijian Lu, Liang Pan

3D object detection using point clouds has attracted increasing attention due to its wide applications in autonomous driving and robotics.

3D Object Detection Autonomous Driving +3

Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation

1 code implementation30 Jul 2022 Gongjie Zhang, Zhipeng Luo, Kaiwen Cui, Shijian Lu, Eric P. Xing

Despite its success, the said paradigm is still constrained by several factors, such as (i) low-quality region proposals for novel classes and (ii) negligence of the inter-class correlation among different classes.

Few-Shot Object Detection Meta-Learning +2

Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion

1 code implementation28 Jul 2022 Gongjie Zhang, Zhipeng Luo, Jiaxing Huang, Shijian Lu, Eric P. Xing

The recently proposed DEtection TRansformer (DETR) has established a fully end-to-end paradigm for object detection.

Object object-detection +1

Accelerating DETR Convergence via Semantic-Aligned Matching

1 code implementation CVPR 2022 Gongjie Zhang, Zhipeng Luo, Yingchen Yu, Kaiwen Cui, Shijian Lu

First, it projects object queries into the same embedding space as encoded image features, where the matching can be accomplished efficiently with aligned semantics.

Object object-detection +1

PTTR: Relational 3D Point Cloud Object Tracking with Transformer

1 code implementation CVPR 2022 Changqing Zhou, Zhipeng Luo, Yueru Luo, Tianrui Liu, Liang Pan, Zhongang Cai, Haiyu Zhao, Shijian Lu

In a point cloud sequence, 3D object tracking aims to predict the location and orientation of an object in the current search point cloud given a template point cloud.

3D Object Tracking Object +3

GenCo: Generative Co-training for Generative Adversarial Networks with Limited Data

1 code implementation4 Oct 2021 Kaiwen Cui, Jiaxing Huang, Zhipeng Luo, Gongjie Zhang, Fangneng Zhan, Shijian Lu

Specifically, we design GenCo, a Generative Co-training network that mitigates the discriminator over-fitting issue by introducing multiple complementary discriminators that provide diverse supervision from multiple distinctive views in training.

Data Augmentation Image Generation

MapRE: An Effective Semantic Mapping Approach for Low-resource Relation Extraction

no code implementations EMNLP 2021 Manqing Dong, Chunguang Pan, Zhipeng Luo

Neural relation extraction models have shown promising results in recent years; however, the model performance drops dramatically given only a few training samples.

Few-Shot Learning Relation +1

AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational Data

1 code implementation9 Sep 2021 Zhipeng Luo, Zhixing He, Jin Wang, Manqing Dong, Jianqiang Huang, Mingjian Chen, Bohang Zheng

Temporal relational data, perhaps the most commonly used data type in industrial machine learning applications, needs labor-intensive feature engineering and data analyzing for giving precise model predictions.

AutoML BIG-bench Machine Learning +1

Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency

1 code implementation ICCV 2021 Zhipeng Luo, Zhongang Cai, Changqing Zhou, Gongjie Zhang, Haiyu Zhao, Shuai Yi, Shijian Lu, Hongsheng Li, Shanghang Zhang, Ziwei Liu

In addition, existing 3D domain adaptive detection methods often assume prior access to the target domain annotations, which is rarely feasible in the real world.

3D Object Detection Autonomous Driving +1

Domain Consistency Regularization for Unsupervised Multi-source Domain Adaptive Classification

no code implementations16 Jun 2021 Zhipeng Luo, Xiaobing Zhang, Shijian Lu, Shuai Yi

Compared with single-source unsupervised domain adaptation (SUDA), domain shift in MUDA exists not only between the source and target domains but also among multiple source domains.

Classification Multi-Source Unsupervised Domain Adaptation +2

DA-DETR: Domain Adaptive Detection Transformer with Information Fusion

no code implementations CVPR 2023 Jingyi Zhang, Jiaxing Huang, Zhipeng Luo, Gongjie Zhang, Xiaoqin Zhang, Shijian Lu

DA-DETR introduces a novel CNN-Transformer Blender (CTBlender) that fuses the CNN features and Transformer features ingeniously for effective feature alignment and knowledge transfer across domains.

Domain Adaptation Object +3

BERT-based Acronym Disambiguation with Multiple Training Strategies

no code implementations25 Feb 2021 Chunguang Pan, Bingyan Song, Shengguang Wang, Zhipeng Luo

Acronym disambiguation (AD) task aims to find the correct expansions of an ambiguous ancronym in a given sentence.

Binary Classification Sentence +1

A Technical Report for VIPriors Image Classification Challenge

no code implementations17 Jul 2020 Zhipeng Luo, Ge Li, Zhiguang Zhang

This paper is a brief report to our submission to the VIPriors Image Classification Challenge.

Classification Ensemble Learning +3

VIPriors Object Detection Challenge

no code implementations16 Jul 2020 Zhipeng Luo, Lixuan Che

This paper is a brief report to our submission to the VIPriors Object Detection Challenge.

Object object-detection +1

Challenge report:VIPriors Action Recognition Challenge

no code implementations16 Jul 2020 Zhipeng Luo, Dawei Xu, Zhiguang Zhang

This paper is a brief report to our submission to the VIPriors Action Recognition Challenge.

Action Recognition

Efficient Architecture Search for Continual Learning

no code implementations7 Jun 2020 Qiang Gao, Zhipeng Luo, Diego Klabjan

To reach these goals, we propose a novel approach named as Continual Learning with Efficient Architecture Search, or CLEAS in short.

Continual Learning Neural Architecture Search +1

PointNLM: Point Nonlocal-Means for vegetation segmentation based on middle echo point clouds

no code implementations20 Jun 2019 Jonathan Li, Rongren Wu, Yiping Chen, Qing Zhu, Zhipeng Luo, Cheng Wang

Second, to accurately extract trees from all point clouds, we propose a 3D deep learning network, PointNLM, to semantically segment tree crowns.

Point Cloud Segmentation Segmentation +1

Learning Fast Matching Models from Weak Annotations

no code implementations30 Jan 2019 Xue Li, Zhipeng Luo, Hao Sun, Jianjin Zhang, Weihao Han, Xianqi Chu, Liangjie Zhang, Qi Zhang

The proposed training framework targets on mitigating both issues, by treating the stronger but undeployable models as annotators, and learning a deployable model from both human provided relevance labels and weakly annotated search log data.

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