484 citations · 504 across the 5 of their papers we have counts for
5 papers
Goal-Driven Autonomous Exploration Through Deep Reinforcement Learning
Reinis Cimurs, Il Hong Suh, Jin Han Lee
In this paper, we present an autonomous navigation system for goal-driven exploration of unknown environments through deep reinforcement learning (DRL). Points of interest (POI) fo…
Acceleration of Actor-Critic Deep Reinforcement Learning for Visual Grasping in Clutter by State Representation Learning Based on Disentanglement of a Raw Input Image
Taewon Kim, Yeseong Park, Youngbin Park +1
For a robotic grasping task in which diverse unseen target objects exist in a cluttered environment, some deep learning-based methods have achieved state-of-the-art results using v…
From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation
Jin Han Lee, Myung-Kyu Han, Dong Wook Ko +1
Estimating accurate depth from a single image is challenging because it is an ill-posed problem as infinitely many 3D scenes can be projected to the same 2D scene. However, recent…
Efficient Feature Matching by Progressive Candidate Search
Sehyung Lee, Jongwoo Lim, Il Hong Suh
We present a novel feature matching algorithm that systematically utilizes the geometric properties of features such as position, scale, and orientation, in addition to the convent…
Tracking Human-like Natural Motion Using Deep Recurrent Neural Networks
Youngbin Park, Sungphill Moon, Il Hong Suh
Kinect skeleton tracker is able to achieve considerable human body tracking performance in convenient and a low-cost manner. However, The tracker often captures unnatural human pos…