255 citations · 855 across the 35 of their papers we have counts for
12 papers · 1 filter
Deep Meta Learning for Real-Time Target-Aware Visual Tracking
Janghoon Choi, Junseok Kwon, Kyoung Mu Lee
In this paper, we propose a novel on-line visual tracking framework based on the Siamese matching network and meta-learner network, which run at real-time speeds. Conventional deep…
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger +21
In this paper, we strive to answer two questions: What is the current state of 3D hand pose estimation from depth images? And, what are the next challenges that need to be tackled?…
Joint Blind Motion Deblurring and Depth Estimation of Light Field
Dongwoo Lee, Haesol Park, In Kyu Park +1
Removing camera motion blur from a single light field is a challenging task since it is highly ill-posed inverse problem. The problem becomes even worse when blur kernel varies spa…
V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map
Gyeongsik Moon, Ju Yong Chang, Kyoung Mu Lee
Most of the existing deep learning-based methods for 3D hand and human pose estimation from a single depth map are based on a common framework that takes a 2D depth map and directl…
Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images
Seung Yeon Shin, Soochahn Lee, Il Dong Yun +2
We propose a framework for localization and classification of masses in breast ultrasound (BUS) images. We have experimentally found that training convolutional neural network base…
Look Wider to Match Image Patches with Convolutional Neural Networks
Haesol Park, Kyoung Mu Lee
When a human matches two images, the viewer has a natural tendency to view the wide area around the target pixel to obtain clues of right correspondence. However, designing a match…
Joint Estimation of Camera Pose, Depth, Deblurring, and Super-Resolution from a Blurred Image Sequence
Haesol Park, Kyoung Mu Lee
The conventional methods for estimating camera poses and scene structures from severely blurry or low resolution images often result in failure. The off-the-shelf deblurring or sup…
Enhanced Deep Residual Networks for Single Image Super-Resolution
Bee Lim, Sanghyun Son, Heewon Kim +2
Recent research on super-resolution has progressed with the development of deep convolutional neural networks (DCNN). In particular, residual learning techniques exhibit improved p…
Holistic Planimetric prediction to Local Volumetric prediction for 3D Human Pose Estimation
Gyeongsik Moon, Ju Yong Chang, Yumin Suh +1
We propose a novel approach to 3D human pose estimation from a single depth map. Recently, convolutional neural network (CNN) has become a powerful paradigm in computer vision. Man…
Online Video Deblurring via Dynamic Temporal Blending Network
Tae Hyun Kim, Kyoung Mu Lee, Bernhard Schölkopf +1
State-of-the-art video deblurring methods are capable of removing non-uniform blur caused by unwanted camera shake and/or object motion in dynamic scenes. However, most existing me…
2D-3D Pose Consistency-based Conditional Random Fields for 3D Human Pose Estimation
Ju Yong Chang, Kyoung Mu Lee
This study considers the 3D human pose estimation problem in a single RGB image by proposing a conditional random field (CRF) model over 2D poses, in which the 3D pose is obtained…
Real-time visual tracking by deep reinforced decision making
Janghoon Choi, Junseok Kwon, Kyoung Mu Lee
One of the major challenges of model-free visual tracking problem has been the difficulty originating from the unpredictable and drastic changes in the appearance of objects we tar…