Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Kun Liu

Kun Liu

Noisy-Labeled NER with Confidence Estimation


Apr 12, 2021
Kun Liu, Yao Fu, Chuanqi Tan, Mosha Chen, Ningyu Zhang, Songfang Huang, Sheng Gao

Figure 1 for Noisy-Labeled NER with Confidence Estimation
Figure 2 for Noisy-Labeled NER with Confidence Estimation
Figure 3 for Noisy-Labeled NER with Confidence Estimation
Figure 4 for Noisy-Labeled NER with Confidence Estimation
* NAACL 2021 Camera Ready 
  Access Paper or Ask Questions

Language Guided Networks for Cross-modal Moment Retrieval


Jun 18, 2020
Kun Liu, Xun Yang, Tat-seng Chua, Huadong Ma, Chuang Gan

Figure 1 for Language Guided Networks for Cross-modal Moment Retrieval
Figure 2 for Language Guided Networks for Cross-modal Moment Retrieval
Figure 3 for Language Guided Networks for Cross-modal Moment Retrieval
Figure 4 for Language Guided Networks for Cross-modal Moment Retrieval

  Access Paper or Ask Questions

A Real-time Action Representation with Temporal Encoding and Deep Compression


Jun 17, 2020
Kun Liu, Wu Liu, Huadong Ma, Mingkui Tan, Chuang Gan

Figure 1 for A Real-time Action Representation with Temporal Encoding and Deep Compression
Figure 2 for A Real-time Action Representation with Temporal Encoding and Deep Compression
Figure 3 for A Real-time Action Representation with Temporal Encoding and Deep Compression
Figure 4 for A Real-time Action Representation with Temporal Encoding and Deep Compression

  Access Paper or Ask Questions

Structural Combinatorial of Network Information System of Systems based on Evolutionary Optimization Method


Feb 22, 2020
Tingting Zhang, Yushi Lan, Aiguo Song, Kun Liu, Nan Wang

Figure 1 for Structural Combinatorial of Network Information System of Systems based on Evolutionary Optimization Method
Figure 2 for Structural Combinatorial of Network Information System of Systems based on Evolutionary Optimization Method
Figure 3 for Structural Combinatorial of Network Information System of Systems based on Evolutionary Optimization Method
Figure 4 for Structural Combinatorial of Network Information System of Systems based on Evolutionary Optimization Method

  Access Paper or Ask Questions

Fine-Grained Instance-Level Sketch-Based Video Retrieval


Feb 21, 2020
Peng Xu, Kun Liu, Tao Xiang, Timothy M. Hospedales, Zhanyu Ma, Jun Guo, Yi-Zhe Song

Figure 1 for Fine-Grained Instance-Level Sketch-Based Video Retrieval
Figure 2 for Fine-Grained Instance-Level Sketch-Based Video Retrieval
Figure 3 for Fine-Grained Instance-Level Sketch-Based Video Retrieval
Figure 4 for Fine-Grained Instance-Level Sketch-Based Video Retrieval

  Access Paper or Ask Questions

PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation


Mar 29, 2019
Fenggen Yu, Kun Liu, Yan Zhang, Chenyang Zhu, Kai Xu

Figure 1 for PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation
Figure 2 for PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation
Figure 3 for PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation
Figure 4 for PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation
* CVPR 2019 
 * CVPR 2019; Corresponding author: Kai Xu ([email protected]); Project page: www.kevinkaixu.net/projects/partnet.html 
  Access Paper or Ask Questions

Solar Cell Surface Defect Inspection Based on Multispectral Convolutional Neural Network


Dec 15, 2018
Haiyong Chen, Yue Pang, Qidi Hu, Kun Liu

Figure 1 for Solar Cell Surface Defect Inspection Based on Multispectral Convolutional Neural Network
Figure 2 for Solar Cell Surface Defect Inspection Based on Multispectral Convolutional Neural Network
Figure 3 for Solar Cell Surface Defect Inspection Based on Multispectral Convolutional Neural Network
Figure 4 for Solar Cell Surface Defect Inspection Based on Multispectral Convolutional Neural Network
* 14 pages, 7 figures,14 tables 
  Access Paper or Ask Questions

Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55


Oct 27, 2017
Li Yi, Lin Shao, Manolis Savva, Haibin Huang, Yang Zhou, Qirui Wang, Benjamin Graham, Martin Engelcke, Roman Klokov, Victor Lempitsky, Yuan Gan, Pengyu Wang, Kun Liu, Fenggen Yu, Panpan Shui, Bingyang Hu, Yan Zhang, Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Minki Jeong, Jaehoon Choi, Changick Kim, Angom Geetchandra, Narasimha Murthy, Bhargava Ramu, Bharadwaj Manda, M Ramanathan, Gautam Kumar, P Preetham, Siddharth Srivastava, Swati Bhugra, Brejesh Lall, Christian Haene, Shubham Tulsiani, Jitendra Malik, Jared Lafer, Ramsey Jones, Siyuan Li, Jie Lu, Shi Jin, Jingyi Yu, Qixing Huang, Evangelos Kalogerakis, Silvio Savarese, Pat Hanrahan, Thomas Funkhouser, Hao Su, Leonidas Guibas

Figure 1 for Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Figure 2 for Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Figure 3 for Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Figure 4 for Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

  Access Paper or Ask Questions

Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data


Oct 20, 2017
Kun Liu, Wu Liu, Huadong Ma, Wenbing Huang, Xiongxiong Dong

Figure 1 for Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data
Figure 2 for Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data
Figure 3 for Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data
Figure 4 for Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data

  Access Paper or Ask Questions

Proceedings of the 2017 AdKDD & TargetAd Workshop


Jul 11, 2017
Abraham Bagherjeiran, Nemanja Djuric, Mihajlo Grbovic, Kuang-Chih Lee, Kun Liu, Vladan Radosavljevic, Suju Rajan

* Workshop Proceedings with links to the accepted papers 
  Access Paper or Ask Questions