b'Jonghyun Choi'

research

∙ 08/28/2023

Online Continual Learning on Hierarchical Label Expansion

Continual learning (CL) enables models to adapt to new tasks and environ...

0 Byung Hyun Lee, et al. ∙

research

∙ 08/18/2023

Multi-Level Compositional Reasoning for Interactive Instruction Following

Robotic agents performing domestic chores by natural language directives...

0 Suvaansh Bhambri, et al. ∙

research

∙ 08/14/2023

Context-Aware Planning and Environment-Aware Memory for Instruction Following Embodied Agents

Accomplishing household tasks requires to plan step-by-step actions cons...

0 Byeonghwi Kim, et al. ∙

research

∙ 08/11/2023

Cost-effective On-device Continual Learning over Memory Hierarchy with Miro

Continual learning (CL) trains NN models incrementally from a continuous...

0 Xinyue Ma, et al. ∙

research

∙ 06/11/2023

EaSyGuide : ESG Issue Identification Framework leveraging Abilities of Generative Large Language Models

This paper presents our participation in the FinNLP-2023 shared task on ...

0 Hanwool Lee, et al. ∙

research

∙ 04/04/2023

MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds

Unsupervised domain adaptation (UDA) addresses the problem of distributi...

0 Ashish Sinha, et al. ∙

research

∙ 11/18/2022

Ask4Help: Learning to Leverage an Expert for Embodied Tasks

Embodied AI agents continue to become more capable every year with the a...

0 Kunal Pratap Singh, et al. ∙

research

∙ 04/26/2022

Attentive Fine-Grained Structured Sparsity for Image Restoration

Image restoration tasks have witnessed great performance improvement in ...

8 Junghun Oh, et al. ∙

research

∙ 03/29/2022

Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries

Learning under a continuously changing data distribution with incorrect ...

3 Jihwan Bang, et al. ∙

research

∙ 12/01/2021

Iconary: A Pictionary-Based Game for Testing Multimodal Communication with Drawings and Text

Communicating with humans is challenging for AIs because it requires a s...

8 Christopher Clark, et al. ∙

research

∙ 10/19/2021

Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference

Despite rapid advances in continual learning, a large body of research i...

21 Hyunseo Koh, et al. ∙

research

∙ 10/17/2021

Self-Supervised Learning for Binary Networks by Joint Classifier Training

Despite the great success of self-supervised learning with large floatin...

32 Dahyun Kim, et al. ∙

research

∙ 10/16/2021

BNAS v2: Learning Architectures for Binary Networks with Empirical Improvements

Backbone architectures of most binary networks are well-known floating p...

22 Dahyun Kim, et al. ∙

research

∙ 10/14/2021

Carousel Memory: Rethinking the Design of Episodic Memory for Continual Learning

Continual Learning (CL) is an emerging machine learning paradigm that ai...

41 Soobee Lee, et al. ∙

research

∙ 08/29/2021

Rethinking Deep Image Prior for Denoising

Deep image prior (DIP) serves as a good inductive bias for diverse inver...

4 Yeonsik Jo, et al. ∙

research

∙ 03/31/2021

Rainbow Memory: Continual Learning with a Memory of Diverse Samples

Continual learning is a realistic learning scenario for AI models. Preva...

27 Jihwan Bang, et al. ∙

research

∙ 12/06/2020

MOCA: A Modular Object-Centric Approach for Interactive Instruction Following

Performing simple household tasks based on language directives is very n...

16 Kunal Pratap Singh, et al. ∙

research

∙ 11/03/2020

Learning Visual Representations for Transfer Learning by Suppressing Texture

Recent literature has shown that features obtained from supervised train...

13 Shlok Mishra, et al. ∙

research

∙ 02/17/2020

Learning Architectures for Binary Networks

Backbone architectures of most binary networks are well-known floating p...

0 Kunal Pratap Singh, et al. ∙

research

∙ 12/03/2019

Learning to Super Resolve Intensity Images from Events

An event camera detects per-pixel intensity difference and produces asyn...

4 S. Mohammad Mostafavi I., et al. ∙

research

∙ 02/28/2019

Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset

As there are increasing needs of sharing data for machine learning, ther...

0 Sanghyun Hong, et al. ∙

research

∙ 02/03/2019

Incremental Learning with Maximum Entropy Regularization: Rethinking Forgetting and Intransigence

Incremental learning suffers from two challenging problems; forgetting o...

0 Dahyun Kim, et al. ∙

research

∙ 01/01/2019

Training with the Invisibles: Obfuscating Images to Share Safely for Learning Visual Recognition Models

High-performance visual recognition systems generally require a large co...

0 Tae-Hoon Kim, et al. ∙

research

∙ 01/03/2018

ScreenerNet: Learning Curriculum for Neural Networks

We propose to learn a curriculum or a syllabus for supervised learning w...

0 Tae-Hoon Kim, et al. ∙

research

∙ 12/05/2017

Structured Set Matching Networks for One-Shot Part Labeling

Diagrams often depict complex phenomena and serve as a good test bed for...

0 Jonghyun Choi, et al. ∙

research

∙ 12/09/2016

ActionFlowNet: Learning Motion Representation for Action Recognition

Even with the recent advances in convolutional neural networks (CNN) in ...

0 Joe Yue-Hei Ng, et al. ∙

research

∙ 04/15/2016

Learning Temporal Regularity in Video Sequences

Perceiving meaningful activities in a long video sequence is a challengi...

0 Mahmudul Hasan, et al. ∙

research

∙ 05/05/2014

Comparing apples to apples in the evaluation of binary coding methods

We discuss methodological issues related to the evaluation of unsupervis...

0 Mohammad Rastegari, et al. ∙

research

∙ 01/21/2014

Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition

To perform unconstrained face recognition robust to variations in illumi...

0 Changxing Ding, et al. ∙

Jonghyun Choi

Featured Co-authors