Byoung-Tak Zhang

research

∙ 09/14/2023

PROGrasp: Pragmatic Human-Robot Communication for Object Grasping

Interactive Object Grasping (IOG) is the task of identifying and graspin...

0 Gi-Cheon Kang, et al. ∙

research

∙ 07/12/2023

GVCCI: Lifelong Learning of Visual Grounding for Language-Guided Robotic Manipulation

Language-Guided Robotic Manipulation (LGRM) is a challenging task as it ...

0 Junghyun Kim, et al. ∙

research

∙ 06/05/2023

Overcoming Weak Visual-Textual Alignment for Video Moment Retrieval

Video moment retrieval (VMR) aims to identify the specific moment in an ...

0 Minjoon Jung, et al. ∙

research

∙ 05/23/2023

L-SA: Learning Under-Explored Targets in Multi-Target Reinforcement Learning

Tasks that involve interaction with various targets are called multi-tar...

0 Kibeom Kim, et al. ∙

research

∙ 04/17/2023

Learning Geometry-aware Representations by Sketching

Understanding geometric concepts, such as distance and shape, is essenti...

0 Hyundo Lee, et al. ∙

research

∙ 11/04/2022

SelecMix: Debiased Learning by Contradicting-pair Sampling

Neural networks trained with ERM (empirical risk minimization) sometimes...

0 Inwoo Hwang, et al. ∙

research

∙ 10/31/2022

DUEL: Adaptive Duplicate Elimination on Working Memory for Self-Supervised Learning

In Self-Supervised Learning (SSL), it is known that frequent occurrences...

1 Won-Seok Choi, et al. ∙

research

∙ 10/23/2022

Modal-specific Pseudo Query Generation for Video Corpus Moment Retrieval

Video corpus moment retrieval (VCMR) is the task to retrieve the most re...

8 Minjoon Jung, et al. ∙

research

∙ 10/20/2022

Robust Imitation via Mirror Descent Inverse Reinforcement Learning

Recently, adversarial imitation learning has shown a scalable reward acq...

0 Dong-Sig Han, et al. ∙

research

∙ 10/17/2022

SGRAM: Improving Scene Graph Parsing via Abstract Meaning Representation

Scene graph is structured semantic representation that can be modeled as...

0 Woo Suk Choi, et al. ∙

research

∙ 09/22/2022

Learning to Write with Coherence From Negative Examples

Coherence is one of the critical factors that determine the quality of w...

0 Seonil Son, et al. ∙

research

∙ 08/09/2022

From Scratch to Sketch: Deep Decoupled Hierarchical Reinforcement Learning for Robotic Sketching Agent

We present an automated learning framework for a robotic sketching agent...

0 Ganghun Lee, et al. ∙

research

∙ 08/09/2022

On the Importance of Critical Period in Multi-stage Reinforcement Learning

The initial years of an infant's life are known as the critical period, ...

1 Junseok Park, et al. ∙

research

∙ 07/31/2022

Cross-Modal Alignment Learning of Vision-Language Conceptual Systems

Human infants learn the names of objects and develop their own conceptua...

0 Taehyeong Kim, et al. ∙

research

∙ 05/25/2022

The Dialog Must Go On: Improving Visual Dialog via Generative Self-Training

Visual dialog (VisDial) is a task of answering a sequence of questions g...

0 Gi-Cheon Kang, et al. ∙

research

∙ 04/22/2022

Hypergraph Transformer: Weakly-supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering

Knowledge-based visual question answering (QA) aims to answer a question...

7 Yu-Jung Heo, et al. ∙

research

∙ 01/12/2022

Toddler-Guidance Learning: Impacts of Critical Period on Multimodal AI Agents

Critical periods are phases during which a toddler's brain develops in s...

3 Junseok Park, et al. ∙

research

∙ 12/11/2021

Smooth-Swap: A Simple Enhancement for Face-Swapping with Smoothness

In recent years, face-swapping models have progressed in generation qual...

0 Jiseob Kim, et al. ∙

research

∙ 10/25/2021

Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning

Learning in a multi-target environment without prior knowledge about the...

0 Kibeom Kim, et al. ∙

research

∙ 10/08/2021

Toward a Human-Level Video Understanding Intelligence

We aim to develop an AI agent that can watch video clips and have a conv...

36 Yu-Jung Heo, et al. ∙

research

∙ 08/11/2021

Mounting Video Metadata on Transformer-based Language Model for Open-ended Video Question Answering

Video question answering has recently received a lot of attention from m...

0 Donggeon Lee, et al. ∙

research

∙ 07/21/2021

CogME: A Novel Evaluation Metric for Video Understanding Intelligence

Developing video understanding intelligence is quite challenging because...

14 Minjung Shin, et al. ∙

research

∙ 06/19/2021

Attend What You Need: Motion-Appearance Synergistic Networks for Video Question Answering

Video Question Answering is a task which requires an AI agent to answer ...

0 Ahjeong Seo, et al. ∙

research

∙ 01/31/2021

M2FN: Multi-step Modality Fusion for Advertisement Image Assessment

Assessing advertisements, specifically on the basis of user preferences ...

0 Kyung-Wha Park, et al. ∙

research

∙ 01/27/2021

Learning task-agnostic representation via toddler-inspired learning

One of the inherent limitations of current AI systems, stemming from the...

0 Kwanyoung Park, et al. ∙

research

∙ 12/02/2020

Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning

Active learning is widely used to reduce labeling effort and training ti...

0 Taehyeong Kim, et al. ∙

research

∙ 11/07/2020

Human-Like Active Learning: Machines Simulating the Human Learning Process

Although the use of active learning to increase learners' engagement has...

0 Jaeseo Lim, et al. ∙

research

∙ 10/27/2020

Co-attentional Transformers for Story-Based Video Understanding

Inspired by recent trends in vision and language learning, we explore ap...

0 Björn Bebensee, et al. ∙

research

∙ 05/28/2020

Pattern Denoising in Molecular Associative Memory using Pairwise Markov Random Field Models

We propose an in silico molecular associative memory model for pattern l...

12 Dharani Punithan, et al. ∙

research

∙ 05/07/2020

DramaQA: Character-Centered Video Story Understanding with Hierarchical QA

Despite recent progress on computer vision and natural language processi...

1 Seongho Choi, et al. ∙

research

∙ 04/14/2020

DialGraph: Sparse Graph Learning Networks for Visual Dialog

Visual dialog is a task of answering a sequence of questions grounded in...

21 Gi-Cheon Kang, et al. ∙

research

∙ 01/17/2020

Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data

Conventional sequential learning methods such as Recurrent Neural Networ...

0 Kyoung-Woon On, et al. ∙

research

∙ 11/08/2019

Ruminating Word Representations with Random Noised Masker

We introduce a training method for both better word representation and p...

0 Hwiyeol Jo, et al. ∙

research

∙ 10/06/2019

Which Ads to Show? Advertisement Image Assessment with Auxiliary Information via Multi-step Modality Fusion

Assessing aesthetic preference is a fundamental task related to human co...

0 Kyung-Wha Park, et al. ∙

research

∙ 07/03/2019

Compositional Structure Learning for Sequential Video Data

Conventional sequential learning methods such as Recurrent Neural Networ...

0 Kyoung-Woon On, et al. ∙

research

∙ 06/03/2019

Encoder-Powered Generative Adversarial Networks

We present an encoder-powered generative adversarial network (EncGAN) th...

0 Jiseob Kim, et al. ∙

research

∙ 05/09/2019

Simulating Problem Difficulty in Arithmetic Cognition Through Dynamic Connectionist Models

The present study aims to investigate similarities between how humans an...

0 Sungjae Cho, et al. ∙

research

∙ 04/01/2019

Constructing Hierarchical Q A Datasets for Video Story Understanding

Video understanding is emerging as a new paradigm for studying human-lik...

0 Yu-Jung Heo, et al. ∙

research

∙ 02/25/2019

Dual Attention Networks for Visual Reference Resolution in Visual Dialog

Visual dialog (VisDial) is a task which requires an AI agent to answer a...

0 Gi-Cheon Kang, et al. ∙

research

∙ 01/20/2019

Data Interpolations in Deep Generative Models under Non-Simply-Connected Manifold Topology

Exploiting the deep generative model's remarkable ability of learning th...

0 Jiseob Kim, et al. ∙

research

∙ 01/20/2019

Visualizing Semantic Structures of Sequential Data by Learning Temporal Dependencies

While conventional methods for sequential learning focus on interaction ...

0 Kyoung-Woon On, et al. ∙

research

∙ 09/21/2018

Multimodal Dual Attention Memory for Video Story Question Answering

We propose a video story question-answering (QA) architecture, Multimoda...

0 Kyung-Min Kim, et al. ∙

research

∙ 05/28/2018

GLAC Net: GLocal Attention Cascading Networks for Multi-image Cued Story Generation

The task of multi-image cued story generation, such as visual storytelli...

0 Taehyeong Kim, et al. ∙

research

∙ 05/21/2018

Bilinear Attention Networks

Attention networks in multimodal learning provide an efficient way to ut...

0 Jin-Hwa Kim, et al. ∙

research

∙ 02/12/2018

Answerer in Questioner's Mind for Goal-Oriented Visual Dialogue

Goal-oriented dialogue has been paid attention for its numerous applicat...

0 Sang-Woo Lee, et al. ∙

research

∙ 12/18/2017

Visual Explanations from Hadamard Product in Multimodal Deep Networks

The visual explanation of learned representation of models helps to unde...

0 Jin-Hwa Kim, et al. ∙

research

∙ 12/15/2017

CoDraw: Visual Dialog for Collaborative Drawing

In this work, we propose a goal-driven collaborative task that contains ...

0 Jin-Hwa Kim, et al. ∙

research

∙ 12/13/2017

Multi-focus Attention Network for Efficient Deep Reinforcement Learning

Deep reinforcement learning (DRL) has shown incredible performance in le...

0 Jinyoung Choi, et al. ∙

research

∙ 07/04/2017

DeepStory: Video Story QA by Deep Embedded Memory Networks

Question-answering (QA) on video contents is a significant challenge for...

0 Kyung-Min Kim, et al. ∙

research

∙ 11/04/2016

Ways of Conditioning Generative Adversarial Networks

The GANs are generative models whose random samples realistically reflec...

0 Hanock Kwak, et al. ∙

Byoung-Tak Zhang

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