Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control
Donyoon Hwang*, Byungkun Lee*, Hojoon Lee, Hyunseung Kim, Jaegul Choo. (* Equal contribution)
ICML'24.
project page / arXiv / code / Bibtex

A simple add-on module which injects convolutions into pretrained ViTs for Visuo-motor Control.

Do’s and Don’ts: Learning Desirable Skills with Instruction Videos
Hyunseung Kim, Byungkun Lee, Hojoon Lee, Dongyoon Hwang, Donghu Kim, Jaegul Choo.
NeurIPS'24.
project page / arXiv / Bibtex

A skill discovery algorithm that learns diverse behaviors while following the behaviors in "do" videos while avoiding the behaviors in "don't" videos.

DISCO-DANCE: Learning to Discover Skills through Guidance
Hyunseung Kim*, Byungkun Lee*, Hojoon Lee, Dongyoon Hwang, Jaegul Choo. (* Equal contribution)
NeurIPS'23.
project page / arXiv / code / Bibtex

An unsupervised skill discovery algorithm, which addresses the limited exploration of previous algorithms through explicit guidance.

SimTPR: On the Importance of Feature Decorrelation for Unsupervised Representation Learning for Reinforcement Learning
Hojoon Lee, Koanho Lee, Dongyoon Hwang, Hyunho Lee, Byungkun Lee, Jaegul Choo.
ICML'23.
arXiv / code / poster / Bibtex

We present a visual pre-training algorithm grounded in self-predictive learning principles tailored for reinforcement learning.

ST-RAP: A Spatio-Temporal Framework for Real Estate Appraisal
Hojoon Lee*, Hawon Jung*, Byungkun Lee*, Jaegul Choo. (* Equal contribution)
CIKM'23 (short).
arXiv / code / poster / Bibtex

We construct a real estate appraisal framework that integrates spatial and temporal aspects, validated using a dataset of 3.6M real estate transactions in South Korea from 2016 to 2020.

DraftRec: Personalized Draft Recommendation for Winning in MOBA Games
Hojoon Lee*, Dongyoon Hwang*, Hyunseung Kim, Byungkun Lee, Jaegul Choo.
WWW'22.
arXiv / code / poster / Bibtex

We gathered data from 280,000 matches played by the top 0.3% rank players in Korea for League of Legends. From this, we developed DraftRec, a personalized champion recommendation system aimed at maximizing players' win rates.