571 citations · 3.6k across the 80 of their papers we have counts for
26 papers · 1 filter
Learning Binary Residual Representations for Domain-specific Video Streaming
Yi-Hsuan Tsai, Ming-Yu Liu, Deqing Sun +2
We study domain-specific video streaming. Specifically, we target a streaming setting where the videos to be streamed from a server to a client are all in the same domain and they…
Scene Parsing with Global Context Embedding
Wei-Chih Hung, Yi-Hsuan Tsai, Xiaohui Shen +4
We present a scene parsing method that utilizes global context information based on both the parametric and non- parametric models. Compared to previous methods that only exploit t…
Progressive Representation Adaptation for Weakly Supervised Object Localization
Dong Li, Jia-Bin Huang, Yali Li +2
We address the problem of weakly supervised object localization where only image-level annotations are available for training object detectors. Numerous methods have been proposed…
Tracking Persons-of-Interest via Unsupervised Representation Adaptation
Shun Zhang, Jia-Bin Huang, Jongwoo Lim +4
Multi-face tracking in unconstrained videos is a challenging problem as faces of one person often appear drastically different in multiple shots due to significant variations in sc…
Integrating Boundary and Center Correlation Filters for Visual Tracking with Aspect Ratio Variation
Feng Li, Yingjie Yao, Peihua Li +3
The aspect ratio variation frequently appears in visual tracking and has a severe influence on performance. Although many correlation filter (CF)-based trackers have also been sugg…
Learning Affinity via Spatial Propagation Networks
Sifei Liu, Shalini De Mello, Jinwei Gu +3
In this paper, we propose spatial propagation networks for learning the affinity matrix for vision tasks. We show that by constructing a row/column linear propagation model, the sp…
Joint Image Filtering with Deep Convolutional Networks
Yijun Li, Jia-Bin Huang, Narendra Ahuja +1
Joint image filters leverage the guidance image as a prior and transfer the structural details from the guidance image to the target image for suppressing noise or enhancing spatia…
Fast and Accurate Image Super-Resolution with Deep Laplacian Pyramid Networks
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja +1
Convolutional neural networks have recently demonstrated high-quality reconstruction for single image super-resolution. However, existing methods often require a large number of ne…
Visual Tracking via Dynamic Graph Learning
Chenglong Li, Liang Lin, Wangmeng Zuo +2
Existing visual tracking methods usually localize a target object with a bounding box, in which the performance of the foreground object trackers or detectors is often affected by…
SegFlow: Joint Learning for Video Object Segmentation and Optical Flow
Jingchun Cheng, Yi-Hsuan Tsai, Shengjin Wang +1
This paper proposes an end-to-end trainable network, SegFlow, for simultaneously predicting pixel-wise object segmentation and optical flow in videos. The proposed SegFlow has two…
Learning to Segment Instances in Videos with Spatial Propagation Network
Jingchun Cheng, Sifei Liu, Yi-Hsuan Tsai +6
We propose a deep learning-based framework for instance-level object segmentation. Our method mainly consists of three steps. First, We train a generic model based on ResNet-101 fo…
Stylizing Face Images via Multiple Exemplars
Yibing Song, Linchao Bao, Shengfeng He +2
We address the problem of transferring the style of a headshot photo to face images. Existing methods using a single exemplar lead to inaccurate results when the exemplar does not…
Video Deblurring via Semantic Segmentation and Pixel-Wise Non-Linear Kernel
Wenqi Ren, Jinshan Pan, Xiaochun Cao +1
Video deblurring is a challenging problem as the blur is complex and usually caused by the combination of camera shakes, object motions, and depth variations. Optical flow can be u…
Unsupervised Domain Adaptation for Face Recognition in Unlabeled Videos
Kihyuk Sohn, Sifei Liu, Guangyu Zhong +3
Despite rapid advances in face recognition, there remains a clear gap between the performance of still image-based face recognition and video-based face recognition, due to the vas…
Unsupervised Representation Learning by Sorting Sequences
Hsin-Ying Lee, Jia-Bin Huang, Maneesh Singh +1
We present an unsupervised representation learning approach using videos without semantic labels. We leverage the temporal coherence as a supervisory signal by formulating represen…
CREST: Convolutional Residual Learning for Visual Tracking
Yibing Song, Chao Ma, Lijun Gong +3
Discriminative correlation filters (DCFs) have been shown to perform superiorly in visual tracking. They only need a small set of training samples from the initial frame to generat…
Robust Visual Tracking via Hierarchical Convolutional Features
Chao Ma, Jia-Bin Huang, Xiaokang Yang +1
In this paper, we propose to exploit the rich hierarchical features of deep convolutional neural networks to improve the accuracy and robustness of visual tracking. Deep neural net…
Adaptive Correlation Filters with Long-Term and Short-Term Memory for Object Tracking
Chao Ma, Jia-Bin Huang, Xiaokang Yang +1
Object tracking is challenging as target objects often undergo drastic appearance changes over time. Recently, adaptive correlation filters have been successfully applied to object…
Learning Structured Semantic Embeddings for Visual Recognition
Dong Li, Hsin-Ying Lee, Jia-Bin Huang +2
Numerous embedding models have been recently explored to incorporate semantic knowledge into visual recognition. Existing methods typically focus on minimizing the distance between…
Universal Style Transfer via Feature Transforms
Yijun Li, Chen Fang, Jimei Yang +3
Universal style transfer aims to transfer arbitrary visual styles to content images. Existing feed-forward based methods, while enjoying the inference efficiency, are mainly limite…
Generative Face Completion
Yijun Li, Sifei Liu, Jimei Yang +1
In this paper, we propose an effective face completion algorithm using a deep generative model. Different from well-studied background completion, the face completion task is more…
Unsupervised Holistic Image Generation from Key Local Patches
Donghoon Lee, Sangdoo Yun, Sungjoon Choi +3
We introduce a new problem of generating an image based on a small number of key local patches without any geometric prior. In this work, key local patches are defined as informati…
Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja +1
Convolutional neural networks have recently demonstrated high-quality reconstruction for single-image super-resolution. In this paper, we propose the Laplacian Pyramid Super-Resolu…
Diversified Texture Synthesis with Feed-forward Networks
Yijun Li, Chen Fang, Jimei Yang +3
Recent progresses on deep discriminative and generative modeling have shown promising results on texture synthesis. However, existing feed-forward based methods trade off generalit…