614 citations · 2.5k across the 63 of their papers we have counts for
6 papers · 2 filters
Text-guided Attention Model for Image Captioning
Jonghwan Mun, Minsu Cho, Bohyung Han
Visual attention plays an important role to understand images and demonstrates its effectiveness in generating natural language descriptions of images. On the other hand, recent st…
Large-Scale Image Retrieval with Attentive Deep Local Features
Hyeonwoo Noh, Andre Araujo, Jack Sim +2
We propose an attentive local feature descriptor suitable for large-scale image retrieval, referred to as DELF (DEep Local Feature). The new feature is based on convolutional neura…
MarioQA: Answering Questions by Watching Gameplay Videos
Jonghwan Mun, Paul Hongsuck Seo, Ilchae Jung +1
We present a framework to analyze various aspects of models for video question answering (VideoQA) using customizable synthetic datasets, which are constructed automatically from g…
Modeling and Propagating CNNs in a Tree Structure for Visual Tracking
Hyeonseob Nam, Mooyeol Baek, Bohyung Han
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…
Training Recurrent Answering Units with Joint Loss Minimization for VQA
Hyeonwoo Noh, Bohyung Han
We propose a novel algorithm for visual question answering based on a recurrent deep neural network, where every module in the network corresponds to a complete answering unit with…
Progressive Attention Networks for Visual Attribute Prediction
Paul Hongsuck Seo, Zhe Lin, Scott Cohen +2
We propose a novel attention model that can accurately attends to target objects of various scales and shapes in images. The model is trained to gradually suppress irrelevant regio…