175 citations · 1.3k across the 83 of their papers we have counts for
14 papers · 1 filter
Improving Distant Supervised Relation Extraction by Dynamic Neural Network
Yanjie Gou, Yinjie Lei, Lingqiao Liu +2
Distant Supervised Relation Extraction (DSRE) is usually formulated as a problem of classifying a bag of sentences that contain two query entities, into the predefined relation cla…
To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions
Junjie Zhang, Lingqiao Liu, Peng Wang +1
Real-world visual data often exhibits a long-tailed distribution, where some ''head'' classes have a large number of samples, yet only a few samples are available for ''tail'' clas…
Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction
Liangyi Kang, Jie Liu, Lingqiao Liu +2
Charge prediction, determining charges for criminal cases by analyzing the textual fact descriptions, is a promising technology in legal assistant systems. In practice, the fact de…
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation
Yu Liu, Lingqiao Liu, Haokui Zhang +2
This paper tackles the problem of video object segmentation. We are specifically concerned with the task of segmenting all pixels of a target object in all frames, given the annota…
Structured Binary Neural Networks for Image Recognition
Bohan Zhuang, Chunhua Shen, Mingkui Tan +3
We propose methods to train convolutional neural networks (CNNs) with both binarized weights and activations, leading to quantized models that are specifically friendly to mobile d…
In defense of OSVOS
Yu Liu, Yutong Dai, Anh-Dzung Doan +2
As a milestone for video object segmentation, one-shot video object segmentation (OSVOS) has achieved a large margin compared to the conventional optical-flow based methods regardi…
Effective Training of Convolutional Neural Networks with Low-bitwidth Weights and Activations
Bohan Zhuang, Jing Liu, Mingkui Tan +3
This paper tackles the problem of training a deep convolutional neural network of both low-bitwidth weights and activations. Optimizing a low-precision network is very challenging…
V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices
Damien Teney, Peng Wang, Jiewei Cao +3
One of the primary challenges faced by deep learning is the degree to which current methods exploit superficial statistics and dataset bias, rather than learning to generalise over…
Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
Dong Gong, Lingqiao Liu, Vuong Le +4
Deep autoencoder has been extensively used for anomaly detection. Training on the normal data, the autoencoder is expected to produce higher reconstruction error for the abnormal i…
A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning
Yinjie Lei, Ziqin Zhou, Pingping Zhang +3
A sketch based 3D shape retrieval
Training Quantized Neural Networks with a Full-precision Auxiliary Module
Bohan Zhuang, Lingqiao Liu, Mingkui Tan +2
In this paper, we seek to tackle a challenge in training low-precision networks: the notorious difficulty in propagating gradient through a low-precision network due to the non-dif…
RPC: A Large-Scale Retail Product Checkout Dataset
Xiu-Shen Wei, Quan Cui, Lei Yang +2
Over recent years, emerging interest has occurred in integrating computer vision technology into the retail industry. Automatic checkout (ACO) is one of the critical problems in th…
Learning Pairwise Relationship for Multi-object Detection in Crowded Scenes
Yu Liu, Lingqiao Liu, Hamid Rezatofighi +3
As the post-processing step for object detection, non-maximum suppression (GreedyNMS) is widely used in most of the detectors for many years. It is efficient and accurate for spars…
Mask-aware networks for crowd counting
Shengqin Jiang, Xiaobo Lu, Yinjie Lei +1
Crowd counting problem aims to count the number of objects within an image or a frame in the videos and is usually solved by estimating the density map generated from the object lo…