Search Results for author: Jianchao Yang

Found 51 papers, 12 papers with code

Dressing in the Wild by Watching Dance Videos

no code implementations29 Mar 2022 Xin Dong, Fuwei Zhao, Zhenyu Xie, Xijin Zhang, Daniel K. Du, Min Zheng, Xiang Long, Xiaodan Liang, Jianchao Yang

While significant progress has been made in garment transfer, one of the most applicable directions of human-centric image generation, existing works overlook the in-the-wild imagery, presenting severe garment-person misalignment as well as noticeable degradation in fine texture details.

Frame Image Generation +1

Online Multi-Granularity Distillation for GAN Compression

1 code implementation ICCV 2021 Yuxi Ren, Jie Wu, Xuefeng Xiao, Jianchao Yang

It reveals that OMGD provides a feasible solution for the deployment of real-time image translation on resource-constrained devices.

Translation

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

no code implementations27 Apr 2021 Chaosheng Dong, Xiaojie Jin, Weihao Gao, Yijia Wang, Hongyi Zhang, Xiang Wu, Jianchao Yang, Xiaobing Liu

Deep learning models in large-scale machine learning systems are often continuously trained with enormous data from production environments.

Human Motion Transfer from Poses in the Wild

no code implementations7 Apr 2020 Jian Ren, Menglei Chai, Sergey Tulyakov, Chen Fang, Xiaohui Shen, Jianchao Yang

In this paper, we tackle the problem of human motion transfer, where we synthesize novel motion video for a target person that imitates the movement from a reference video.

Translation

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

1 code implementation ICLR 2020 Jieru Mei, Yingwei Li, Xiaochen Lian, Xiaojie Jin, Linjie Yang, Alan Yuille, Jianchao Yang

We propose a fine-grained search space comprised of atomic blocks, a minimal search unit that is much smaller than the ones used in recent NAS algorithms.

Neural Architecture Search

Neural Epitome Search for Architecture-Agnostic Network Compression

no code implementations ICLR 2020 Daquan Zhou, Xiaojie Jin, Qibin Hou, Kaixin Wang, Jianchao Yang, Jiashi Feng

The recent WSNet [1] is a new model compression method through sampling filterweights from a compact set and has demonstrated to be effective for 1D convolutionneural networks (CNNs).

Model Compression Neural Architecture Search

EnlightenGAN: Deep Light Enhancement without Paired Supervision

8 code implementations17 Jun 2019 Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang

Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data?

Image Restoration Low-Light Image Enhancement

Slimmable Neural Networks

3 code implementations ICLR 2019 Jiahui Yu, Linjie Yang, Ning Xu, Jianchao Yang, Thomas Huang

Instead of training individual networks with different width configurations, we train a shared network with switchable batch normalization.

Instance Segmentation Keypoint Detection +2

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

4 code implementations ECCV 2018 Ning Xu, Linjie Yang, Yuchen Fan, Jianchao Yang, Dingcheng Yue, Yuchen Liang, Brian Price, Scott Cohen, Thomas Huang

End-to-end sequential learning to explore spatial-temporal features for video segmentation is largely limited by the scale of available video segmentation datasets, i. e., even the largest video segmentation dataset only contains 90 short video clips.

One-shot visual object segmentation Optical Flow Estimation +4

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

no code implementations CVPR 2019 Jian Ren, Zhe Li, Jianchao Yang, Ning Xu, Tianbao Yang, David J. Foran

In this paper, we propose an Ecologically-Inspired GENetic (EIGEN) approach that uses the concept of succession, extinction, mimicry, and gene duplication to search neural network structure from scratch with poorly initialized simple network and few constraints forced during the evolution, as we assume no prior knowledge about the task domain.

Factorized Adversarial Networks for Unsupervised Domain Adaptation

no code implementations4 Jun 2018 Jian Ren, Jianchao Yang, Ning Xu, David J. Foran

In this paper, we propose Factorized Adversarial Networks (FAN) to solve unsupervised domain adaptation problems for image classification tasks.

General Classification Image Classification +1

Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences

no code implementations31 Jan 2018 Zhengyuan Yang, Yuncheng Li, Jianchao Yang, Jiebo Luo

The attention mechanism is important for skeleton based action recognition because there exist spatio-temporal key stages while the joint predictions can be inaccurate.

Action Recognition Skeleton Based Action Recognition

Learning $3$D-FilterMap for Deep Convolutional Neural Networks

no code implementations5 Jan 2018 Yingzhen Yang, Jianchao Yang, Ning Xu, Wei Han

Due to the weight sharing scheme, the parameter size of the $3$D-FilterMap is much smaller than that of the filters to be learned in the conventional convolution layer when $3$D-FilterMap generates the same number of filters.

Learning to Segment Human by Watching YouTube

no code implementations4 Oct 2017 Xiaodan Liang, Yunchao Wei, Liang Lin, Yunpeng Chen, Xiaohui Shen, Jianchao Yang, Shuicheng Yan

An intuition on human segmentation is that when a human is moving in a video, the video-context (e. g., appearance and motion clues) may potentially infer reasonable mask information for the whole human body.

Human Detection Semantic Segmentation +3

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

no code implementations10 Sep 2017 Bowen Cheng, Zhangyang Wang, Zhaobin Zhang, Zhu Li, Ding Liu, Jianchao Yang, Shuai Huang, Thomas S. Huang

Emotion recognition from facial expressions is tremendously useful, especially when coupled with smart devices and wireless multimedia applications.

Emotion Recognition Super-Resolution

On the Suboptimality of Proximal Gradient Descent for $\ell^{0}$ Sparse Approximation

no code implementations5 Sep 2017 Yingzhen Yang, Jiashi Feng, Nebojsa Jojic, Jianchao Yang, Thomas S. Huang

We study the proximal gradient descent (PGD) method for $\ell^{0}$ sparse approximation problem as well as its accelerated optimization with randomized algorithms in this paper.

Compressive Sensing Dimensionality Reduction

Learning from Noisy Labels with Distillation

no code implementations ICCV 2017 Yuncheng Li, Jianchao Yang, Yale Song, Liangliang Cao, Jiebo Luo, Li-Jia Li

The ability of learning from noisy labels is very useful in many visual recognition tasks, as a vast amount of data with noisy labels are relatively easy to obtain.

Dense Captioning with Joint Inference and Visual Context

1 code implementation CVPR 2017 Linjie Yang, Kevin Tang, Jianchao Yang, Li-Jia Li

The goal is to densely detect visual concepts (e. g., objects, object parts, and interactions between them) from images, labeling each with a short descriptive phrase.

Robust Single Image Super-Resolution via Deep Networks With Sparse Prior

1 code implementation journals 2016 Ding Liu, Zhaowen Wang, Bihan Wen, Student Member, Jianchao Yang, Member, Wei Han, and Thomas S. Huang, Fellow, IEEE

We demonstrate that a sparse coding model particularly designed for SR can be incarnated as a neural network with the merit of end-to-end optimization over training data.

Image Super-Resolution

Deep Edge Guided Recurrent Residual Learning for Image Super-Resolution

no code implementations29 Apr 2016 Wenhan Yang, Jiashi Feng, Jianchao Yang, Fang Zhao, Jiaying Liu, Zongming Guo, Shuicheng Yan

To address this essentially ill-posed problem, we introduce a Deep Edge Guided REcurrent rEsidual~(DEGREE) network to progressively recover the high-frequency details.

Image Super-Resolution

Human Parsing With Contextualized Convolutional Neural Network

no code implementations ICCV 2015 Xiaodan Liang, Chunyan Xu, Xiaohui Shen, Jianchao Yang, Si Liu, Jinhui Tang, Liang Lin, Shuicheng Yan

In this work, we address the human parsing task with a novel Contextualized Convolutional Neural Network (Co-CNN) architecture, which well integrates the cross-layer context, global image-level context, within-super-pixel context and cross-super-pixel neighborhood context into a unified network.

Human Parsing

Learning with $\ell^{0}$-Graph: $\ell^{0}$-Induced Sparse Subspace Clustering

no code implementations28 Oct 2015 Yingzhen Yang, Jiashi Feng, Jianchao Yang, Thomas S. Huang

Sparse subspace clustering methods, such as Sparse Subspace Clustering (SSC) \cite{ElhamifarV13} and $\ell^{1}$-graph \cite{YanW09, ChengYYFH10}, are effective in partitioning the data that lie in a union of subspaces.

Robust Image Sentiment Analysis Using Progressively Trained and Domain Transferred Deep Networks

no code implementations20 Sep 2015 Quanzeng You, Jiebo Luo, Hailin Jin, Jianchao Yang

Sentiment analysis of such large scale visual content can help better extract user sentiments toward events or topics, such as those in image tweets, so that prediction of sentiment from visual content is complementary to textual sentiment analysis.

Sentiment Analysis

Deep Networks for Image Super-Resolution with Sparse Prior

no code implementations ICCV 2015 Zhaowen Wang, Ding Liu, Jianchao Yang, Wei Han, Thomas Huang

We show that a sparse coding model particularly designed for super-resolution can be incarnated as a neural network, and trained in a cascaded structure from end to end.

Image Restoration Image Super-Resolution

DeepFont: Identify Your Font from An Image

1 code implementation12 Jul 2015 Zhangyang Wang, Jianchao Yang, Hailin Jin, Eli Shechtman, Aseem Agarwala, Jonathan Brandt, Thomas S. Huang

As font is one of the core design concepts, automatic font identification and similar font suggestion from an image or photo has been on the wish list of many designers.

Domain Adaptation Font Recognition +1

Fine-Grained Recognition Without Part Annotations

no code implementations CVPR 2015 Jonathan Krause, Hailin Jin, Jianchao Yang, Li Fei-Fei

Scaling up fine-grained recognition to all domains of fine-grained objects is a challenge the computer vision community will need to face in order to realize its goal of recognizing all object categories.

Intra-Frame Deblurring by Leveraging Inter-Frame Camera Motion

no code implementations CVPR 2015 Haichao Zhang, Jianchao Yang

The proposed method effectively leverages the information distributed across multiple video frames due to camera motion, jointly estimating the motion between consecutive frames and blur within each frame.

Deblurring Frame

Matching-CNN Meets KNN: Quasi-Parametric Human Parsing

no code implementations CVPR 2015 Si Liu, Xiaodan Liang, Luoqi Liu, Xiaohui Shen, Jianchao Yang, Changsheng Xu, Liang Lin, Xiaochun Cao, Shuicheng Yan

Under the classic K Nearest Neighbor (KNN)-based nonparametric framework, the parametric Matching Convolutional Neural Network (M-CNN) is proposed to predict the matching confidence and displacements of the best matched region in the testing image for a particular semantic region in one KNN image.

Human Parsing

Designing A Composite Dictionary Adaptively From Joint Examples

no code implementations12 Mar 2015 Zhangyang Wang, Yingzhen Yang, Jianchao Yang, Thomas S. Huang

We study the complementary behaviors of external and internal examples in image restoration, and are motivated to formulate a composite dictionary design framework.

Image Denoising Image Restoration +1

Deep Human Parsing with Active Template Regression

1 code implementation9 Mar 2015 Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Jian Dong, Liang Lin, Shuicheng Yan

The first CNN network is with max-pooling, and designed to predict the template coefficients for each label mask, while the second CNN network is without max-pooling to preserve sensitivity to label mask position and accurately predict the active shape parameters.

Human Parsing

Learning Super-Resolution Jointly from External and Internal Examples

no code implementations3 Mar 2015 Zhangyang Wang, Yingzhen Yang, Zhaowen Wang, Shiyu Chang, Jianchao Yang, Thomas S. Huang

Single image super-resolution (SR) aims to estimate a high-resolution (HR) image from a lowresolution (LR) input.

Image Super-Resolution

Collaborative Feature Learning from Social Media

no code implementations CVPR 2015 Chen Fang, Hailin Jin, Jianchao Yang, Zhe Lin

We validate our feature learning paradigm on this dataset and find that the learned feature significantly outperforms the state-of-the-art image features in learning better image similarities.

Scale Adaptive Blind Deblurring

no code implementations NeurIPS 2014 Haichao Zhang, Jianchao Yang

The presence of noise and small scale structures usually leads to large kernel estimation errors in blind image deblurring empirically, if not a total failure.

Blind Image Deblurring Image Deblurring

Towards Unified Human Parsing and Pose Estimation

no code implementations CVPR 2014 Jian Dong, Qiang Chen, Xiaohui Shen, Jianchao Yang, Shuicheng Yan

We study the problem of human body configuration analysis, more specifically, human parsing and human pose estimation.

Human Parsing Pose Estimation

Large-Scale Visual Font Recognition

no code implementations CVPR 2014 Guang Chen, Jianchao Yang, Hailin Jin, Jonathan Brandt, Eli Shechtman, Aseem Agarwala, Tony X. Han

This paper addresses the large-scale visual font recognition (VFR) problem, which aims at automatic identification of the typeface, weight, and slope of the text in an image or photo without any knowledge of content.

Font Recognition Image Categorization +1

Scalable Similarity Learning using Large Margin Neighborhood Embedding

no code implementations24 Apr 2014 Zhaowen Wang, Jianchao Yang, Zhe Lin, Jonathan Brandt, Shiyu Chang, Thomas Huang

In this paper, we present an image similarity learning method that can scale well in both the number of images and the dimensionality of image descriptors.

Metric Learning

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

no code implementations21 Dec 2013 Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin, Thomas Huang

The ability to train large-scale neural networks has resulted in state-of-the-art performance in many areas of computer vision.

Exemplar-Based Face Parsing

no code implementations CVPR 2013 Brandon M. Smith, Li Zhang, Jonathan Brandt, Zhe Lin, Jianchao Yang

Given a test image, our algorithm first selects a subset of exemplar images from the database, Our algorithm then computes a nonrigid warp for each exemplar image to align it with the test image.

Face Alignment Face Parsing +1

Fast Image Super-Resolution Based on In-Place Example Regression

no code implementations CVPR 2013 Jianchao Yang, Zhe Lin, Scott Cohen

Extensive experiments on benchmark and realworld images demonstrate that our algorithm can produce natural-looking results with sharp edges and preserved fine details, while the current state-of-the-art algorithms are prone to visual artifacts.

Image Super-Resolution

Probabilistic Elastic Matching for Pose Variant Face Verification

no code implementations CVPR 2013 Haoxiang Li, Gang Hua, Zhe Lin, Jonathan Brandt, Jianchao Yang

By augmenting each feature with its location, a Gaussian mixture model (GMM) is trained to capture the spatialappearance distribution of all face images in the training corpus.

Face Recognition Face Verification

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