b'Jianchao Yang'

research

∙ 03/29/2022

Dressing in the Wild by Watching Dance Videos

While significant progress has been made in garment transfer, one of the...

Xin Dong, et al. ∙

research

∙ 08/16/2021

Online Multi-Granularity Distillation for GAN Compression

Generative Adversarial Networks (GANs) have witnessed prevailing success...

Yuxi Ren, et al. ∙

research

∙ 04/27/2021

One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning

Deep learning models in large-scale machine learning systems are often c...

Chaosheng Dong, et al. ∙

research

∙ 04/07/2020

Human Motion Transfer from Poses in the Wild

In this paper, we tackle the problem of human motion transfer, where we ...

Jian Ren, et al. ∙

research

∙ 12/20/2019

AtomNAS: Fine-Grained End-to-End Neural Architecture Search

Designing of search space is a critical problem for neural architecture ...

Jieru Mei, et al. ∙

research

∙ 07/12/2019

Deep Model Compression via Filter Auto-sampling

The recent WSNet [1] is a new model compression method through sampling ...

Daquan Zhou, et al. ∙

research

∙ 06/17/2019

EnlightenGAN: Deep Light Enhancement without Paired Supervision

Deep learning-based methods have achieved remarkable success in image re...

Yifan Jiang, et al. ∙

research

∙ 12/21/2018

Slimmable Neural Networks

We present a simple and general method to train a single neural network ...

Jiahui Yu, et al. ∙

research

∙ 09/06/2018

YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark

Learning long-term spatial-temporal features are critical for many video...

Ning Xu, et al. ∙

research

∙ 09/03/2018

YouTube-VOS: Sequence-to-Sequence Video Object Segmentation

Learning long-term spatial-temporal features are critical for many video...

Ning Xu, et al. ∙

research

∙ 08/27/2018

Wide Activation for Efficient and Accurate Image Super-Resolution

In this report we demonstrate that with same parameters and computationa...

Jiahui Yu, et al. ∙

research

∙ 06/05/2018

EIGEN: Ecologically-Inspired GENetic Approach for Neural Network Structure Searching

Designing the structure of neural networks is considered one of the most...

Jian Ren, et al. ∙

research

∙ 06/04/2018

Factorized Adversarial Networks for Unsupervised Domain Adaptation

In this paper, we propose Factorized Adversarial Networks (FAN) to solve...

Jian Ren, et al. ∙

research

∙ 02/04/2018

Efficient Video Object Segmentation via Network Modulation

Video object segmentation targets at segmenting a specific object throug...

Linjie Yang, et al. ∙

research

∙ 01/31/2018

Action Recognition with Visual Attention on Skeleton Images

Action recognition with 3D skeleton sequences is becoming popular due to...

Zhengyuan Yang, et al. ∙

research

∙ 01/05/2018

Learning 3D-FilterMap for Deep Convolutional Neural Networks

We present a novel and compact architecture for deep Convolutional Neura...

Yingzhen Yang, et al. ∙

research

∙ 11/28/2017

WSNet: Compact and Efficient Networks with Weight Sampling

We present a new approach and a novel architecture, termed WSNet, for le...

Xiaojie Jin, et al. ∙

research

∙ 10/04/2017

Learning to Segment Human by Watching YouTube

An intuition on human segmentation is that when a human is moving in a v...

Xiaodan Liang, et al. ∙

research

∙ 09/10/2017

Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach

Emotion recognition from facial expressions is tremendously useful, espe...

Bowen Cheng, et al. ∙

research

∙ 03/13/2017

GUN: Gradual Upsampling Network for single image super-resolution

In this paper, we propose an efficient super-resolution (SR) method base...

fcq, et al. ∙

research

∙ 03/12/2017

Local Patch Classification Based Framework for Single Image Super-Resolution

Recent learning-based super-resolution (SR) methods often focus on the d...

fcq, et al. ∙

research

∙ 03/07/2017

Learning from Noisy Labels with Distillation

The ability of learning from noisy labels is very useful in many visual ...

Yuncheng Li, et al. ∙

research

∙ 11/21/2016

Dense Captioning with Joint Inference and Visual Context

Dense captioning is a newly emerging computer vision topic for understan...

Linjie Yang, et al. ∙

research

∙ 09/09/2015

Proposal-free Network for Instance-level Object Segmentation

Instance-level object segmentation is an important yet under-explored ta...

Xiaodan Liang, et al. ∙

research

∙ 07/31/2015

Deep Networks for Image Super-Resolution with Sparse Prior

Deep learning techniques have been successfully applied in many areas of...

Zhaowen Wang, et al. ∙

research

∙ 07/12/2015

DeepFont: Identify Your Font from An Image

As font is one of the core design concepts, automatic font identificatio...

Zhangyang Wang, et al. ∙

research

∙ 04/22/2015

Self-Tuned Deep Super Resolution

Deep learning has been successfully applied to image super resolution (S...

Zhangyang Wang, et al. ∙

research

∙ 04/06/2015

Matching-CNN Meets KNN: Quasi-Parametric Human Parsing

Both parametric and non-parametric approaches have demonstrated encourag...

Si Liu, et al. ∙

research

∙ 03/31/2015

Real-World Font Recognition Using Deep Network and Domain Adaptation

We address a challenging fine-grain classification problem: recognizing ...

Zhangyang Wang, et al. ∙

research

∙ 03/12/2015

Designing A Composite Dictionary Adaptively From Joint Examples

We study the complementary behaviors of external and internal examples i...

Zhangyang Wang, et al. ∙

research

∙ 03/09/2015

Deep Human Parsing with Active Template Regression

In this work, the human parsing task, namely decomposing a human image i...

Xiaodan Liang, et al. ∙

research

∙ 03/03/2015

Learning Super-Resolution Jointly from External and Internal Examples

Single image super-resolution (SR) aims to estimate a high-resolution (H...

Zhangyang Wang, et al. ∙

research

∙ 02/05/2015

Collaborative Feature Learning from Social Media

Image feature representation plays an essential role in image recognitio...

Chen Fang, et al. ∙

research

∙ 12/18/2014

Decomposition-Based Domain Adaptation for Real-World Font Recognition

We present a domain adaption framework to address a domain mismatch betw...

Zhangyang Wang, et al. ∙

research

∙ 04/24/2014

Scalable Similarity Learning using Large Margin Neighborhood Embedding

Classifying large-scale image data into object categories is an importan...

Zhaowen Wang, et al. ∙

research

∙ 12/21/2013

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

The ability to train large-scale neural networks has resulted in state-o...

Thomas Paine, et al. ∙

Jianchao Yang

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