• Publications
  • Influence
Learning Multi-domain Convolutional Neural Networks for Visual Tracking
  • H. Nam, B. Han
  • Computer Science
  • IEEE Conference on Computer Vision and Pattern…
  • 27 October 2015
We propose a novel visual tracking algorithm based on the representations from a discriminatively trained Convolutional Neural Network (CNN). Our algorithm pretrains a CNN using a large set of videosExpand
  • 1,310
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The Visual Object Tracking VOT2016 Challenge Results
The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers areExpand
  • 436
  • 145
Learning Deconvolution Network for Semantic Segmentation
We propose a novel semantic segmentation algorithm by learning a deep deconvolution network. We learn the network on top of the convolutional layers adopted from VGG 16-layer net. The deconvolutionExpand
  • 1,320
  • 86
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network
We propose an online visual tracking algorithm by learning discriminative saliency map using Convolutional Neural Network (CNN). Given a CNN pre-trained on a large-scale image repository in offline,Expand
  • 534
  • 65
Large-Scale Image Retrieval with Attentive Deep Local Features
We propose an attentive local feature descriptor suitable for large-scale image retrieval, referred to as DELE (DEep Local Feature). The new feature is based on convolutional neural networks, whichExpand
  • 217
  • 47
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking
We present an online visual tracking algorithm by managing multiple target appearance models in a tree structure. The proposed algorithm employs Convolutional Neural Networks (CNNs) to representExpand
  • 215
  • 29
Weakly Supervised Action Localization by Sparse Temporal Pooling Network
We propose a weakly supervised temporal action localization algorithm on untrimmed videos using convolutional neural networks. Our algorithm learns from video-level class labels and predicts temporalExpand
  • 92
  • 21
Real-Time MDNet
We present a fast and accurate visual tracking algorithm based on the multi-domain convolutional neural network (MDNet). The proposed approach accelerates feature extraction procedure and learns moreExpand
  • 79
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Image Question Answering Using Convolutional Neural Network with Dynamic Parameter Prediction
We tackle image question answering (ImageQA) problem by learning a convolutional neural network (CNN) with a dynamic parameter layer whose weights are determined adaptively based on questions. ForExpand
  • 228
  • 17
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
We propose a novel deep neural network architecture for semi-supervised semantic segmentation using heterogeneous annotations. Contrary to existing approaches posing semantic segmentation as a singleExpand
  • 230
  • 16