3.2k citations · 12.3k across the 227 of their papers we have counts for
13 papers · 1 filter
Towards Arbitrary-View Face Alignment by Recommendation Trees
Shizhan Zhu, Cheng Li, Chen Change Loy +1
Learning to simultaneously handle face alignment of arbitrary views, e.g. frontal and profile views, appears to be more challenging than we thought. The difficulties lay in i) acco…
WIDER FACE: A Face Detection Benchmark
Shuo Yang, Ping Luo, Chen Change Loy +1
Face detection is one of the most studied topics in the computer vision community. Much of the progresses have been made by the availability of face detection benchmark datasets. W…
An Empirical Study of Recent Face Alignment Methods
Heng Yang, Xuhui Jia, Chen Change Loy +1
The problem of face alignment has been intensively studied in the past years. A large number of novel methods have been proposed and reported very good performance on benchmark dat…
Semantic Image Segmentation via Deep Parsing Network
Ziwei Liu, Xiaoxiao Li, Ping Luo +2
This paper addresses semantic image segmentation by incorporating rich information into Markov Random Field (MRF), including high-order relations and mixture of label contexts. Unl…
From Facial Parts Responses to Face Detection: A Deep Learning Approach
Shuo Yang, Ping Luo, Chen Change Loy +1
In this paper, we propose a novel deep convolutional network (DCN) that achieves outstanding performance on FDDB, PASCAL Face, and AFW. Specifically, our method achieves a high rec…
Learning Social Relation Traits from Face Images
Zhanpeng Zhang, Ping Luo, Chen Change Loy +1
Social relation defines the association, e.g, warm, friendliness, and dominance, between two or more people. Motivated by psychological studies, we investigate if such fine-grained…
Boosting Optical Character Recognition: A Super-Resolution Approach
Chao Dong, Ximei Zhu, Yubin Deng +2
Text image super-resolution is a challenging yet open research problem in the computer vision community. In particular, low-resolution images hamper the performance of typical opti…
A Large-Scale Car Dataset for Fine-Grained Categorization and Verification
Linjie Yang, Ping Luo, Chen Change Loy +1
Updated on 24/09/2015: This update provides preliminary experiment results for fine-grained classification on the surveillance data of CompCars. The train/test splits are provided…
Reading Scene Text in Deep Convolutional Sequences
Pan He, Weilin Huang, Yu Qiao +2
We develop a Deep-Text Recurrent Network (DTRN) that regards scene text reading as a sequence labelling problem. We leverage recent advances of deep convolutional neural networks t…
Compression Artifacts Reduction by a Deep Convolutional Network
Chao Dong, Yubin Deng, Chen Change Loy +1
Lossy compression introduces complex compression artifacts, particularly the blocking artifacts, ringing effects and blurring. Existing algorithms either focus on removing blocking…
Learning from Multiple Sources for Video Summarisation
Xiatian Zhu, Chen Change Loy, Shaogang Gong
Many visual surveillance tasks, e.g.video summarisation, is conventionally accomplished through analysing imagerybased features. Relying solely on visual cues for public surveillan…
Defining Chaos
Brian R. Hunt, Edward Ott
In this paper we propose, discuss and illustrate a computationally feasible definition of chaos which can be applied very generally to situations that are commonly encountered, inc…
Image Super-Resolution Using Deep Convolutional Networks
Chao Dong, Chen Change Loy, Kaiming He +1
We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is re…