activity
20152022
most citedMMDetection: Open MMLab Detection Toolbox and Benchmark

794 citations · 1.5k across the 20 of their papers we have counts for

collaborators

20 papers

cs.CV2022★ 5 cited

Real-time Online Multi-Object Tracking in Compressed Domain

Qiankun Liu, Bin Liu, Yue Wu +2

Recent online Multi-Object Tracking (MOT) methods have achieved desirable tracking performance. However, the tracking speed of most existing methods is rather slow. Inspired from t…

cs.CV2021

LineCounter: Learning Handwritten Text Line Segmentation by Counting

Deng Li, Yue Wu, Yicong Zhou

Handwritten Text Line Segmentation (HTLS) is a low-level but important task for many higher-level document processing tasks like handwritten text recognition. It is often formulate…

cs.CV2020★ 23 cited

Cross-modality Person re-identification with Shared-Specific Feature Transfer

Yan Lu, Yue Wu, Bin Liu +4

Cross-modality person re-identification (cm-ReID) is a challenging but key technology for intelligent video analysis. Existing works mainly focus on learning common representation…

cs.CV2019★ 794 cited

MMDetection: Open MMLab Detection Toolbox and Benchmark

Kai Chen, Jiaqi Wang, Jiangmiao Pang +22

We present MMDetection, an object detection toolbox that contains a rich set of object detection and instance segmentation methods as well as related components and modules. The to…

cs.CV2019★ 2 cited

Large Scale Incremental Learning

Yue Wu, Yinpeng Chen, Lijuan Wang +4

Modern machine learning suffers from catastrophic forgetting when learning new classes incrementally. The performance dramatically degrades due to the missing data of old classes.…

cs.CV2019

Spatially Constrained GAN for Face and Fashion Synthesis

Songyao Jiang, Hongfu Liu, Yue Wu +1

Image generation has raised tremendous attention in both academic and industrial areas, especially for the conditional and target-oriented image generation, such as criminal portra…

cs.CV2019★ 40 cited

Rethinking Classification and Localization for Object Detection

Yue Wu, Yinpeng Chen, Lu Yuan +4

Two head structures (i.e. fully connected head and convolution head) have been widely used in R-CNN based detectors for classification and localization tasks. However, there is a l…

cs.LG2018★ 1 cited

Predictive Local Smoothness for Stochastic Gradient Methods

Jun Li, Hongfu Liu, Bineng Zhong +2

Stochastic gradient methods are dominant in nonconvex optimization especially for deep models but have low asymptotical convergence due to the fixed smoothness. To address this pro…

cs.CV2018★ 412 cited

Facial Landmark Detection: a Literature Survey

Yue Wu, Qiang Ji

The locations of the fiducial facial landmark points around facial components and facial contour capture the rigid and non-rigid facial deformations due to head movements and facia…

cs.CV2018★ 93 cited

Incremental Classifier Learning with Generative Adversarial Networks

Yue Wu, Yinpeng Chen, Lijuan Wang +5

In this paper, we address the incremental classifier learning problem, which suffers from catastrophic forgetting. The main reason for catastrophic forgetting is that the past data…

cs.LG2018★ 6 cited

Clustering with Outlier Removal

Hongfu Liu, Jun Li, Yue Wu +1

Cluster analysis and outlier detection are strongly coupled tasks in data mining area. Cluster structure can be easily destroyed by few outliers; on the contrary, outliers are defi…

cs.CV2017★ 19 cited

Simultaneous Facial Landmark Detection, Pose and Deformation Estimation under Facial Occlusion

Yue Wu, Chao Gou, Qiang Ji

Facial landmark detection, head pose estimation, and facial deformation analysis are typical facial behavior analysis tasks in computer vision. The existing methods usually perform…

cs.CV2017★ 2 cited

Constrained Joint Cascade Regression Framework for Simultaneous Facial Action Unit Recognition and Facial Landmark Detection

Yue Wu, Qiang Ji

Cascade regression framework has been shown to be effective for facial landmark detection. It starts from an initial face shape and gradually predicts the face shape update from th…

cs.CV2017

Constrained Deep Transfer Feature Learning and its Applications

Yue Wu, Qiang Ji

Feature learning with deep models has achieved impressive results for both data representation and classification for various vision tasks. Deep feature learning, however, typicall…

cs.CV2017★ 1 cited

Robust Facial Landmark Detection under Significant Head Poses and Occlusion

Yue Wu, Qiang Ji

There have been tremendous improvements for facial landmark detection on general "in-the-wild" images. However, it is still challenging to detect the facial landmarks on images wit…

cs.CV2017

A Hierarchical Probabilistic Model for Facial Feature Detection

Yue Wu, Ziheng Wang, Qiang Ji

Facial feature detection from facial images has attracted great attention in the field of computer vision. It is a nontrivial task since the appearance and shape of the face tend t…

cs.CV2017★ 1 cited

Facial Feature Tracking under Varying Facial Expressions and Face Poses based on Restricted Boltzmann Machines

Yue Wu, Zuoguan Wang, Qiang Ji

Facial feature tracking is an active area in computer vision due to its relevance to many applications. It is a nontrivial task, since faces may have varying facial expressions, po…

eess.SY2017

Convergence Analysis and Design of Multi-block ADMM via Switched Control Theory

Jun Li, Hongfu Liu, Yue Wu +1

We consider three challenges in multi-block Alternating Direction Method of Multipliers (ADMM): building convergence conditions for ADMM with any block (variable) sequence, finding…

cs.CV2016★ 82 cited

Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks

Joseph P. Robinson, Ming Shao, Yue Wu +1

We present the largest kinship recognition dataset to date, Families in the Wild (FIW). Motivated by the lack of a single, unified dataset for kinship recognition, we aim to provid…

cs.CV2015★ 63 cited

LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks

Steven C. H. Hoi, Xiongwei Wu, Hantang Liu +4

Logo detection from images has many applications, particularly for brand recognition and intellectual property protection. Most existing studies for logo recognition and detection…