activity
20172022
most citedA Neural Dirichlet Process Mixture Model for Task-Free Continual Learning

94 citations · 138 across the 8 of their papers we have counts for

collaborators

16 papers

cs.LG202212 cited

Variational Laplace Autoencoders

Yookoon Park, Chris Dongjoo Kim, Gunhee Kim

Variational autoencoders employ an amortized inference model to approximate the posterior of latent variables. However, such amortized variational inference faces two challenges: (…

cs.CV20221 cited

Panoramic Vision Transformer for Saliency Detection in 360° Videos

Heeseung Yun, Sehun Lee, Gunhee Kim

360 video saliency detection is one of the challenging benchmarks for 360 video understanding since non-negligible distortion and discontinuity occur in the project…

cs.CV2020

Parameter Efficient Multimodal Transformers for Video Representation Learning

Sangho Lee, Youngjae Yu, Gunhee Kim +3

The recent success of Transformers in the language domain has motivated adapting it to a multimodal setting, where a new visual model is trained in tandem with an already pretraine…

cs.CV2020

CurlingNet: Compositional Learning between Images and Text for Fashion IQ Data

Youngjae Yu, Seunghwan Lee, Yuncheol Choi +1

We present an approach named CurlingNet that can measure the semantic distance of composition of image-text embedding. In order to learn an effective image-text composition for the…

cs.LG202094 cited

A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning

Soochan Lee, Junsoo Ha, Dongsu Zhang +1

Despite the growing interest in continual learning, most of its contemporary works have been studied in a rather restricted setting where tasks are clearly distinguishable, and tas…

cs.CL20195 cited

Discovery of Natural Language Concepts in Individual Units of CNNs

Seil Na, Yo Joong Choe, Dong-Hyun Lee +1

Although deep convolutional networks have achieved improved performance in many natural language tasks, they have been treated as black boxes because they are difficult to interpre…