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20162021
most citedTsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning

19 citations · 44 across the 13 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.RO2018★ 1 cited

Interactive Text2Pickup Network for Natural Language based Human-Robot Collaboration

Hyemin Ahn, Sungjoon Choi, Nuri Kim +2

In this paper, we propose the Interactive Text2Pickup (IT2P) network for human-robot collaboration which enables an effective interaction with a human user despite the ambiguity in…

cs.LG2018★ 3 cited

Maximum Causal Tsallis Entropy Imitation Learning

Kyungjae Lee, Sungjoon Choi, Songhwai Oh

In this paper, we propose a novel maximum causal Tsallis entropy (MCTE) framework for imitation learning which can efficiently learn a sparse multi-modal policy distribution from d…

cs.CV2018★ 1 cited

Learning Instance-Aware Object Detection Using Determinantal Point Processes

Nuri Kim, Donghoon Lee, Songhwai Oh

Recent object detectors find instances while categorizing candidate regions. As each region is evaluated independently, the number of candidate regions from a detector is usually l…

cs.CV2018★ 1 cited

Deep Pose Consensus Networks

Geonho Cha, Minsik Lee, Jungchan Cho +1

In this paper, we address the problem of estimating a 3D human pose from a single image, which is important but difficult to solve due to many reasons, such as self-occlusions, wil…

cs.CV2018★ 11 cited

Generative Single Image Reflection Separation

Donghoon Lee, Ming-Hsuan Yang, Songhwai Oh

Single image reflection separation is an ill-posed problem since two scenes, a transmitted scene and a reflected scene, need to be inferred from a single observation. To make the p…