b'Xiaoou Tang'

research

∙ 05/18/2020

InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs

Although Generative Adversarial Networks (GANs) have made significant pr...

Yujun Shen, et al. ∙

research

∙ 07/25/2019

Interpreting the Latent Space of GANs for Semantic Face Editing

Despite the recent advance of Generative Adversarial Networks (GANs) in ...

Yujun Shen, et al. ∙

research

∙ 04/23/2019

Path-Restore: Learning Network Path Selection for Image Restoration

Very deep Convolutional Neural Networks (CNNs) have greatly improved the...

Xintao Wang, et al. ∙

research

∙ 04/22/2019

Switchable Whitening for Deep Representation Learning

Normalization methods are essential components in convolutional neural n...

Xingang Pan, et al. ∙

research

∙ 03/15/2019

A Lightweight Optical Flow CNN - Revisiting Data Fidelity and Regularization

Over four decades, the majority addresses the problem of optical flow es...

Tak-Wai Hui, et al. ∙

research

∙ 01/23/2019

DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images

Understanding fashion images has been advanced by benchmarks with rich a...

Yuying Ge, et al. ∙

research

∙ 12/05/2018

Feature Matters: A Stage-by-Stage Approach for Knowledge Transfer

Convolutional Neural Networks (CNNs) become deeper and deeper in recent ...

Mengya Gao, et al. ∙

research

∙ 12/04/2018

FaceFeat-GAN: a Two-Stage Approach for Identity-Preserving Face Synthesis

The advance of Generative Adversarial Networks (GANs) enables realistic ...

Yujun Shen, et al. ∙

research

∙ 11/26/2018

Deep Network Interpolation for Continuous Imagery Effect Transition

Deep convolutional neural network has demonstrated its capability of lea...

Xintao Wang, et al. ∙

research

∙ 09/07/2018

Improving On-policy Learning with Statistical Reward Accumulation

Deep reinforcement learning has obtained significant breakthroughs in re...

Yubin Deng, et al. ∙

research

∙ 09/01/2018

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

The Super-Resolution Generative Adversarial Network (SRGAN) is a seminal...

Xintao Wang, et al. ∙

research

∙ 07/25/2018

Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net

Convolutional neural networks (CNNs) have achieved great successes in ma...

Xingang Pan, et al. ∙

research

∙ 06/01/2018

Deep Imbalanced Learning for Face Recognition and Attribute Prediction

Data for face analysis often exhibit highly-skewed class distribution, i...

Chen Huang, et al. ∙

research

∙ 05/18/2018

LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation

FlowNet2, the state-of-the-art convolutional neural network (CNN) for op...

Tak-Wai Hui, et al. ∙

research

∙ 03/02/2018

Pose-Robust Face Recognition via Deep Residual Equivariant Mapping

Face recognition achieves exceptional success thanks to the emergence of...

Kaidi Cao, et al. ∙

research

∙ 12/17/2017

Spatial As Deep: Spatial CNN for Traffic Scene Understanding

Convolutional neural networks (CNNs) are usually built by stacking convo...

Xingang Pan, et al. ∙

research

∙ 12/02/2017

Mix-and-Match Tuning for Self-Supervised Semantic Segmentation

Deep convolutional networks for semantic image segmentation typically re...

Xiaohang Zhan, et al. ∙

research

∙ 08/09/2017

Learning to Disambiguate by Asking Discriminative Questions

The ability to ask questions is a powerful tool to gather information in...

Yining Li, et al. ∙

research

∙ 08/07/2017

Unconstrained Fashion Landmark Detection via Hierarchical Recurrent Transformer Networks

Fashion landmarks are functional key points defined on clothes, such as ...

Sijie Yan, et al. ∙

research

∙ 08/01/2017

Video Object Segmentation with Re-identification

Conventional video segmentation methods often rely on temporal continuit...

Xiaoxiao Li, et al. ∙

research

∙ 07/29/2017

Recurrent Scale Approximation for Object Detection in CNN

Since convolutional neural network (CNN) lacks an inherent mechanism to ...

Yu Liu, et al. ∙

research

∙ 07/17/2017

Aesthetic-Driven Image Enhancement by Adversarial Learning

We introduce EnhanceGAN, an adversarial learning based model that perfor...

Yubin Deng, et al. ∙

research

∙ 06/09/2017

Face Detection through Scale-Friendly Deep Convolutional Networks

In this paper, we share our experience in designing a convolutional netw...

Shuo Yang, et al. ∙

research

∙ 05/08/2017

Temporal Segment Networks for Action Recognition in Videos

Deep convolutional networks have achieved great success for image recogn...

Limin Wang, et al. ∙

research

∙ 04/05/2017

Not All Pixels Are Equal: Difficulty-aware Semantic Segmentation via Deep Layer Cascade

We propose a novel deep layer cascade (LC) method to improve the accurac...

Xiaoxiao Li, et al. ∙

research

∙ 03/08/2017

A Pursuit of Temporal Accuracy in General Activity Detection

Detecting activities in untrimmed videos is an important but challenging...

Yuanjun Xiong, et al. ∙

research

∙ 02/08/2017

Video Frame Synthesis using Deep Voxel Flow

We address the problem of synthesizing new video frames in an existing v...

Ziwei Liu, et al. ∙

research

∙ 01/29/2017

Faceness-Net: Face Detection through Deep Facial Part Responses

We propose a deep convolutional neural network (CNN) for face detection ...

Shuo Yang, et al. ∙

research

∙ 10/27/2016

Local Similarity-Aware Deep Feature Embedding

Existing deep embedding methods in vision tasks are capable of learning ...

Chen Huang, et al. ∙

research

∙ 10/04/2016

Image Aesthetic Assessment: An Experimental Survey

This survey aims at reviewing recent computer vision techniques used in ...

Yubin Deng, et al. ∙

research

∙ 09/21/2016

From Facial Expression Recognition to Interpersonal Relation Prediction

Interpersonal relation defines the association, e.g., warm, friendliness...

Zhanpeng Zhang, et al. ∙

research

∙ 09/07/2016

Deep Markov Random Field for Image Modeling

Markov Random Fields (MRFs), a formulation widely used in generative ima...

Zhirong Wu, et al. ∙

research

∙ 08/10/2016

Fashion Landmark Detection in the Wild

Visual fashion analysis has attracted many attentions in the recent year...

Ziwei Liu, et al. ∙

research

∙ 08/09/2016

Deep Convolution Networks for Compression Artifacts Reduction

Lossy compression introduces complex compression artifacts, particularly...

Chao Dong, et al. ∙

research

∙ 08/02/2016

Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

Deep convolutional networks have achieved great success for visual recog...

Limin Wang, et al. ∙

research

∙ 08/02/2016

CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016

This paper presents the method that underlies our submission to the untr...

Yuanjun Xiong, et al. ∙

research

∙ 08/01/2016

Accelerating the Super-Resolution Convolutional Neural Network

As a successful deep model applied in image super-resolution (SR), the S...

Chao Dong, et al. ∙

research

∙ 06/23/2016

Deep Learning Markov Random Field for Semantic Segmentation

Semantic segmentation tasks can be well modeled by Markov Random Field (...

Ziwei Liu, et al. ∙

research

∙ 04/25/2016

Actionness Estimation Using Hybrid Fully Convolutional Networks

Actionness was introduced to quantify the likelihood of containing a gen...

Limin Wang, et al. ∙

research

∙ 02/03/2016

Discriminative Sparse Neighbor Approximation for Imbalanced Learning

Data imbalance is common in many vision tasks where one or more classes ...

Chen Huang, et al. ∙

research

∙ 12/07/2015

Sparsifying Neural Network Connections for Face Recognition

This paper proposes to learn high-performance deep ConvNets with sparse ...

Yi Sun, et al. ∙

research

∙ 11/19/2015

Adjustable Bounded Rectifiers: Towards Deep Binary Representations

Binary representation is desirable for its memory efficiency, computatio...

Zhirong Wu, et al. ∙

research

∙ 09/14/2015

Learning Social Relation Traits from Face Images

Social relation defines the association, e.g, warm, friendliness, and do...

Zhanpeng Zhang, et al. ∙

research

∙ 09/09/2015

Semantic Image Segmentation via Deep Parsing Network

This paper addresses semantic image segmentation by incorporating rich i...

Ziwei Liu, et al. ∙

research

∙ 06/30/2015

A Large-Scale Car Dataset for Fine-Grained Categorization and Verification

Updated on 24/09/2015: This update provides preliminary experiment resul...

Linjie Yang, et al. ∙

research

∙ 06/14/2015

Reading Scene Text in Deep Convolutional Sequences

We develop a Deep-Text Recurrent Network (DTRN) that regards scene text ...

Pan He, et al. ∙

research

∙ 04/27/2015

Compression Artifacts Reduction by a Deep Convolutional Network

Lossy compression introduces complex compression artifacts, particularly...

Chao Dong, et al. ∙

research

∙ 02/03/2015

DeepID3: Face Recognition with Very Deep Neural Networks

The state-of-the-art of face recognition has been significantly advanced...

Yi Sun, et al. ∙

research

∙ 01/05/2015

Learning to Recognize Pedestrian Attribute

Learning to recognize pedestrian attributes at far distance is a challen...

Yubin Deng, et al. ∙

research

∙ 12/31/2014

Image Super-Resolution Using Deep Convolutional Networks

We propose a deep learning method for single image super-resolution (SR)...

Chao Dong, et al. ∙

Xiaoou Tang

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