Search Results for author: Qiao Liu

Found 23 papers, 12 papers with code

Synergistic Anchored Contrastive Pre-training for Few-Shot Relation Extraction

1 code implementation19 Dec 2023 Da Luo, Yanglei Gan, Rui Hou, Run Lin, Qiao Liu, Yuxiang Cai, Wannian Gao

Specifically, our framework involves a symmetrical contrastive objective that encompasses both sentence-anchored and label-anchored contrastive losses.

Contrastive Learning Relation +2

Aspect-oriented Opinion Alignment Network for Aspect-Based Sentiment Classification

1 code implementation22 Aug 2023 Xueyi Liu, Rui Hou, Yanglei Gan, Da Luo, Changlin Li, Xiaojun Shi, Qiao Liu

In addition, we design a multi-perspective attention mechanism that align relevant opinion information with respect to the given aspect.

Management Sentiment Analysis +1

Language-Enhanced Session-Based Recommendation with Decoupled Contrastive Learning

no code implementations20 Jul 2023 Zhipeng Zhang, Piao Tong, Yingwei Ma, Qiao Liu, Xujiang Liu, Xu Luo

Furthermore, we introduce a novel Decoupled Contrastive Learning method to enhance the effectiveness of the language representation.

Contrastive Learning Retrieval +1

CausalEGM: a general causal inference framework by encoding generative modeling

2 code implementations8 Dec 2022 Qiao Liu, Zhongren Chen, Wing Hung Wong

In this article, we develop a general framework $\textit{CausalEGM}$ for estimating causal effects by encoding generative modeling, which can be applied in both binary and continuous treatment settings.

Causal Inference

Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems

no code implementations23 Nov 2022 Jirong Yi, Qiaosheng Zhang, Zhen Chen, Qiao Liu, Wei Shao, Yusen He, Yaohua Wang

We first argue that the MSE minimization approach is equivalent to a conditional entropy learning problem, and then propose a mutual information learning formulation for solving regression problems by using a reparameterization technique.


Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems

no code implementations3 Oct 2022 Jirong Yi, Qiaosheng Zhang, Zhen Chen, Qiao Liu, Wei Shao

Deep learning systems have been reported to acheive state-of-the-art performances in many applications, and one of the keys for achieving this is the existence of well trained classifiers on benchmark datasets which can be used as backbone feature extractors in downstream tasks.

Binary Classification Data Augmentation

Pose-Aided Video-based Person Re-Identification via Recurrent Graph Convolutional Network

no code implementations23 Sep 2022 Honghu Pan, Qiao Liu, Yongyong Chen, Yunqi He, Yuan Zheng, Feng Zheng, Zhenyu He

Finally, we propose a dual-attention method consisting of node-attention and time-attention to obtain the temporal graph representation from the node embeddings, where the self-attention mechanism is employed to learn the importance of each node and each frame.

Retrieval Video-Based Person Re-Identification +1

Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems

no code implementations21 Sep 2022 Jirong Yi, Qiaosheng Zhang, Zhen Chen, Qiao Liu, Wei Shao

Deep learning systems have been reported to achieve state-of-the-art performances in many applications, and a key is the existence of well trained classifiers on benchmark datasets.

Binary Classification

Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applications

no code implementations17 Feb 2022 Kexin Ding, Mu Zhou, Zichen Wang, Qiao Liu, Corey W. Arnold, Shaoting Zhang, Dimitri N. Metaxas

Image-based characterization and disease understanding involve integrative analysis of morphological, spatial, and topological information across biological scales.

An Informative Tracking Benchmark

1 code implementation13 Dec 2021 Xin Li, Qiao Liu, Wenjie Pei, Qiuhong Shen, YaoWei Wang, Huchuan Lu, Ming-Hsuan Yang

Along with the rapid progress of visual tracking, existing benchmarks become less informative due to redundancy of samples and weak discrimination between current trackers, making evaluations on all datasets extremely time-consuming.

Visual Tracking

Active Learning for Deep Visual Tracking

no code implementations17 Oct 2021 Di Yuan, Xiaojun Chang, Yi Yang, Qiao Liu, Dehua Wang, Zhenyu He

In this paper, we propose an active learning method for deep visual tracking, which selects and annotates the unlabeled samples to train the deep CNNs model.

Active Learning Visual Tracking

Boost Neural Networks by Checkpoints

no code implementations NeurIPS 2021 Feng Wang, Guoyizhe Wei, Qiao Liu, Jinxiang Ou, Xian Wei, Hairong Lv

In the experiments, it yields up to 5. 02% higher accuracy over single EfficientNet-B0 on the imbalanced datasets.

Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion

1 code implementation27 Apr 2021 Guanglin Niu, Yang Li, Chengguang Tang, Ruiying Geng, Jian Dai, Qiao Liu, Hao Wang, Jian Sun, Fei Huang, Luo Si

Moreover, modeling and inferring complex relations of one-to-many (1-N), many-to-one (N-1), and many-to-many (N-N) by previous knowledge graph completion approaches requires high model complexity and a large amount of training instances.

Few-Shot Learning Relational Reasoning

Reinforced Molecular Optimization with Neighborhood-Controlled Grammars

1 code implementation NeurIPS 2020 Chencheng Xu, Qiao Liu, Minlie Huang, Tao Jiang

A major challenge in the pharmaceutical industry is to design novel molecules with specific desired properties, especially when the property evaluation is costly.

 Ranked #1 on Molecular Graph Generation on ZINC (QED Top-3 metric)

Graph Generation Molecular Graph Generation

LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark

1 code implementation3 Aug 2020 Qiao Liu, Xin Li, Zhenyu He, Chenglong Li, Jun Li, Zikun Zhou, Di Yuan, Jing Li, Kai Yang, Nana Fan, Feng Zheng

We evaluate and analyze more than 30 trackers on LSOTB-TIR to provide a series of baselines, and the results show that deep trackers achieve promising performance.

Thermal Infrared Object Tracking Vocal Bursts Intensity Prediction

Accurate Bounding-box Regression with Distance-IoU Loss for Visual Tracking

no code implementations3 Jul 2020 Di Yuan, Xiu Shu, Nana Fan, Xiaojun Chang, Qiao Liu, Zhenyu He

Moreover, we introduce a classification part that is trained online and optimized with a Conjugate-Gradient-based strategy to guarantee real-time tracking speed.

regression Visual Tracking

Multi-Task Driven Feature Models for Thermal Infrared Tracking

1 code implementation26 Nov 2019 Qiao Liu, Xin Li, Zhenyu He, Nana Fan, Di Yuan, Wei Liu, Yonsheng Liang

These two feature models are learned using a multi-task matching framework and are jointly optimized on the TIR tracking task.

Thermal Infrared Object Tracking

Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking

1 code implementation9 Jun 2019 Qiao Liu, Xin Li, Zhenyu He, Nana Fan, Di Yuan, Hongpeng Wang

These two similarities complement each other and hence enhance the discriminative capacity of the network for handling distractors.

Semantic Similarity Thermal Infrared Object Tracking

PTB-TIR: A Thermal Infrared Pedestrian Tracking Benchmark

1 code implementation18 Jan 2018 Qiao Liu, Zhenyu He, Xin Li, Yuan Zheng

The ability to evaluate the TIR pedestrian tracker fairly, on a benchmark dataset, is significant for the development of this field.

Attribute Thermal Infrared Object Tracking

Generalized Graph Embedding Models

no code implementations ICLR 2018 Qiao Liu, Xiao-Hui Yang, Rui Wan, Shouzhong Tu, Zufeng Wu

Many types of relations in physical, biological, social and information systems can be modeled as homogeneous or heterogeneous concept graphs.

General Classification Graph Embedding +2

Hierarchical Spatial-aware Siamese Network for Thermal Infrared Object Tracking

1 code implementation27 Nov 2017 Xin Li, Qiao Liu, Nana Fan, Zhenyu He, Hongzhi Wang

In this paper, we cast the TIR tracking problem as a similarity verification task, which is coupled well to the objective of the tracking task.

General Classification Thermal Infrared Object Tracking

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