619 citations · 6.4k across the 178 of their papers we have counts for
37 papers · 1 filter
Weaving Multi-scale Context for Single Shot Detector
Yunpeng Chen, Jianshu Li, Bin Zhou +2
Aggregating context information from multiple scales has been proved to be effective for improving accuracy of Single Shot Detectors (SSDs) on object detection. However, existing m…
Nonconvex Sparse Spectral Clustering by Alternating Direction Method of Multipliers and Its Convergence Analysis
Canyi Lu, Jiashi Feng, Zhouchen Lin +1
Spectral Clustering (SC) is a widely used data clustering method which first learns a low-dimensional embedding of data by computing the eigenvectors of the normalized Laplacia…
Personalized and Occupational-aware Age Progression by Generative Adversarial Networks
Siyu Zhou, Weiqiang Zhao, Jiashi Feng +4
Face age progression, which aims to predict the future looks, is important for various applications and has been received considerable attentions. Existing methods and datasets are…
HashGAN:Attention-aware Deep Adversarial Hashing for Cross Modal Retrieval
Xi Zhang, Siyu Zhou, Jiashi Feng +5
As the rapid growth of multi-modal data, hashing methods for cross-modal retrieval have received considerable attention. Deep-networks-based cross-modal hashing methods are appeali…
Integrated Face Analytics Networks through Cross-Dataset Hybrid Training
Jianshu Li, Shengtao Xiao, Fang Zhao +5
Face analytics benefits many multimedia applications. It consists of a number of tasks, such as facial emotion recognition and face parsing, and most existing approaches generally…
Predicting Scene Parsing and Motion Dynamics in the Future
Xiaojie Jin, Huaxin Xiao, Xiaohui Shen +6
The ability of predicting the future is important for intelligent systems, e.g. autonomous vehicles and robots to plan early and make decisions accordingly. Future scene parsing an…
WSNet: Compact and Efficient Networks Through Weight Sampling
Xiaojie Jin, Yingzhen Yang, Ning Xu +4
We present a new approach and a novel architecture, termed WSNet, for learning compact and efficient deep neural networks. Existing approaches conventionally learn full model param…
Transferable Semi-supervised Semantic Segmentation
Huaxin Xiao, Yunchao Wei, Yu Liu +2
The performance of deep learning based semantic segmentation models heavily depends on sufficient data with careful annotations. However, even the largest public datasets only prov…
Deep Sparse Subspace Clustering
Xi Peng, Jiashi Feng, Shijie Xiao +3
In this paper, we present a deep extension of Sparse Subspace Clustering, termed Deep Sparse Subspace Clustering (DSSC). Regularized by the unit sphere distribution assumption for…
Discriminative Similarity for Clustering and Semi-Supervised Learning
Yingzhen Yang, Feng Liang, Nebojsa Jojic +3
Similarity-based clustering and semi-supervised learning methods separate the data into clusters or classes according to the pairwise similarity between the data, and the pairwise…
On the Suboptimality of Proximal Gradient Descent for Sparse Approximation
Yingzhen Yang, Jiashi Feng, Nebojsa Jojic +2
We study the proximal gradient descent (PGD) method for sparse approximation problem as well as its accelerated optimization with randomized algorithms in this paper. We…
Self-explanatory Deep Salient Object Detection
Huaxin Xiao, Jiashi Feng, Yunchao Wei +1
Salient object detection has seen remarkable progress driven by deep learning techniques. However, most of deep learning based salient object detection methods are black-box in nat…
Learning with Rethinking: Recurrently Improving Convolutional Neural Networks through Feedback
Xin Li, Zequn Jie, Jiashi Feng +2
Recent years have witnessed the great success of convolutional neural network (CNN) based models in the field of computer vision. CNN is able to learn hierarchically abstracted fea…
FoveaNet: Perspective-aware Urban Scene Parsing
Xin Li, Zequn Jie, Wei Wang +7
Parsing urban scene images benefits many applications, especially self-driving. Most of the current solutions employ generic image parsing models that treat all scales and location…
A Simple Loss Function for Improving the Convergence and Accuracy of Visual Question Answering Models
Ilija Ilievski, Jiashi Feng
Visual question answering as recently proposed multimodal learning task has enjoyed wide attention from the deep learning community. Lately, the focus was on developing new represe…
Stochastic Primal-Dual Proximal ExtraGradient Descent for Compositely Regularized Optimization
Tianyi Lin, Linbo Qiao, Teng Zhang +2
We consider a wide range of regularized stochastic minimization problems with two regularization terms, one of which is composed with a linear function. This optimization model abs…
Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization
Canyi Lu, Jiashi Feng, Yudong Chen +3
This paper studies the Tensor Robust Principal Component (TRPCA) problem which extends the known Robust PCA (Candes et al. 2011) to the tensor case. Our model is based on a new ten…
Dual Path Networks
Yunpeng Chen, Jianan Li, Huaxin Xiao +3
In this work, we present a simple, highly efficient and modularized Dual Path Network (DPN) for image classification which presents a new topology of connection paths internally. B…
Neural Person Search Machines
Hao Liu, Jiashi Feng, Zequn Jie +5
We investigate the problem of person search in the wild in this work. Instead of comparing the query against all candidate regions generated in a query-blind manner, we propose to…
Perceptual Generative Adversarial Networks for Small Object Detection
Jianan Li, Xiaodan Liang, Yunchao Wei +3
Detecting small objects is notoriously challenging due to their low resolution and noisy representation. Existing object detection pipelines usually detect small objects through le…
A Unified Framework for Stochastic Matrix Factorization via Variance Reduction
Renbo Zhao, William B. Haskell, Jiashi Feng
We propose a unified framework to speed up the existing stochastic matrix factorization (SMF) algorithms via variance reduction. Our framework is general and it subsumes several we…
IAN: The Individual Aggregation Network for Person Search
Jimin Xiao, Yanchun Xie, Tammam Tillo +3
Person search in real-world scenarios is a new challenging computer version task with many meaningful applications. The challenge of this task mainly comes from: (1) unavailable bo…
Generative Partition Networks for Multi-Person Pose Estimation
Xuecheng Nie, Jiashi Feng, Junliang Xing +1
This paper proposes a new Generative Partition Network (GPN) to address the challenging multi-person pose estimation problem. Different from existing models that are either complet…
Multiple-Human Parsing in the Wild
Jianshu Li, Jian Zhao, Yunchao Wei +5
Human parsing is attracting increasing research attention. In this work, we aim to push the frontier of human parsing by introducing the problem of multi-human parsing in the wild.…