Search Results for author: Hyojin Bahng

Found 7 papers, 6 papers with code

Exploring Visual Prompts for Adapting Large-Scale Models

1 code implementation31 Mar 2022 Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan, Phillip Isola

The surprising effectiveness of visual prompting provides a new perspective on adapting pre-trained models in vision.

Exploring Unlabeled Faces for Novel Attribute Discovery

1 code implementation CVPR 2020 Hyojin Bahng, Sunghyo Chung, Seungjoo Yoo, Jaegul Choo

Despite remarkable success in unpaired image-to-image translation, existing systems still require a large amount of labeled images.

Image-to-Image Translation Translation

ST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed

1 code implementation29 Nov 2019 Cheonbok Park, Chunggi Lee, Hyojin Bahng, Yunwon Tae, Kihwan Kim, Seungmin Jin, Sungahn Ko, Jaegul Choo

Predicting road traffic speed is a challenging task due to different types of roads, abrupt speed change and spatial dependencies between roads; it requires the modeling of dynamically changing spatial dependencies among roads and temporal patterns over long input sequences.

Graph Attention

Learning De-biased Representations with Biased Representations

2 code implementations ICML 2020 Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun, Jaegul Choo, Seong Joon Oh

This tactic is feasible in many scenarios where it is much easier to define a set of biased representations than to define and quantify bias.

Coloring With Limited Data: Few-Shot Colorization via Memory-Augmented Networks

1 code implementation9 Jun 2019 Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung, Junsoo Lee, Jaehyuk Chang, Jaegul Choo

Despite recent advancements in deep learning-based automatic colorization, they are still limited when it comes to few-shot learning.

Colorization Few-Shot Learning

Coloring with Words: Guiding Image Colorization Through Text-based Palette Generation

1 code implementation ECCV 2018 Hyojin Bahng, Seungjoo Yoo, Wonwoong Cho, David K. Park, Ziming Wu, Xiaojuan Ma, Jaegul Choo

This paper proposes a novel approach to generate multiple color palettes that reflect the semantics of input text and then colorize a given grayscale image according to the generated color palette.

Colorization Image Colorization

Cannot find the paper you are looking for? You can Submit a new open access paper.