3.2k citations · 12.3k across the 227 of their papers we have counts for
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PolyNet: A Pursuit of Structural Diversity in Very Deep Networks
Xingcheng Zhang, Zhizhong Li, Chen Change Loy +1
A number of studies have shown that increasing the depth or width of convolutional networks is a rewarding approach to improve the performance of image recognition. In our study, h…
Local Similarity-Aware Deep Feature Embedding
Chen Huang, Chen Change Loy, Xiaoou Tang
Existing deep embedding methods in vision tasks are capable of learning a compact Euclidean space from images, where Euclidean distances correspond to a similarity metric. To make…
Image Aesthetic Assessment: An Experimental Survey
Yubin Deng, Chen Change Loy, Xiaoou Tang
This survey aims at reviewing recent computer vision techniques used in the assessment of image aesthetic quality. Image aesthetic assessment aims at computationally distinguishing…
From Facial Expression Recognition to Interpersonal Relation Prediction
Zhanpeng Zhang, Ping Luo, Chen Change Loy +1
Interpersonal relation defines the association, e.g., warm, friendliness, and dominance, between two or more people. Motivated by psychological studies, we investigate if such fine…
Deep Convolution Networks for Compression Artifacts Reduction
Ke Yu, Chao Dong, Chen Change Loy +1
Lossy compression introduces complex compression artifacts, particularly blocking artifacts, ringing effects and blurring. Existing algorithms either focus on removing blocking art…
Accelerating the Super-Resolution Convolutional Neural Network
Chao Dong, Chen Change Loy, Xiaoou Tang
As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) has demonstrated superior performance to the previous h…
Deep Cascaded Bi-Network for Face Hallucination
Shizhan Zhu, Sifei Liu, Chen Change Loy +1
We present a novel framework for hallucinating faces of unconstrained poses and with very low resolution (face size as small as 5pxIOD). In contrast to existing studies that mostly…
Deep Learning Markov Random Field for Semantic Segmentation
Ziwei Liu, Xiaoxiao Li, Ping Luo +2
Semantic segmentation tasks can be well modeled by Markov Random Field (MRF). This paper addresses semantic segmentation by incorporating high-order relations and mixture of label…
Discriminative Sparse Neighbor Approximation for Imbalanced Learning
Chen Huang, Chen Change Loy, Xiaoou Tang
Data imbalance is common in many vision tasks where one or more classes are rare. Without addressing this issue conventional methods tend to be biased toward the majority class wit…