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20182025
most citedST-GRAT: A Novel Spatio-temporal Graph Attention Network for Accurately Forecasting Dynamically Changing Road Speed

177 citations · 387 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CV2025

Cycle Consistency as Reward: Learning Image-Text Alignment without Human Preferences

Hyojin Bahng, Caroline Chan, Fredo Durand +1

Measuring alignment between language and vision is a fundamental challenge, especially as multimodal data becomes increasingly detailed and complex. Existing methods often rely on…

cs.CV2022★ 107 cited

Exploring Visual Prompts for Adapting Large-Scale Models

Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan +1

We investigate the efficacy of visual prompting to adapt large-scale models in vision. Following the recent approach from prompt tuning and adversarial reprogramming, we learn a si…

cs.CV2019

Exploring Unlabeled Faces for Novel Attribute Discovery

Hyojin Bahng, Sunghyo Chung, Seungjoo Yoo +1

Despite remarkable success in unpaired image-to-image translation, existing systems still require a large amount of labeled images. This is a bottleneck for their real-world applic…

cs.CV2019★ 99 cited

Learning De-biased Representations with Biased Representations

Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun +2

Many machine learning algorithms are trained and evaluated by splitting data from a single source into training and test sets. While such focus on in-distribution learning scenario…

cs.CV2019

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

Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung +3

Despite recent advancements in deep learning-based automatic colorization, they are still limited when it comes to few-shot learning. Existing models require a significant amount o…

cs.CV2018

MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation

David Keetae Park, Seungjoo Yoo, Hyojin Bahng +2

Recently, generative adversarial networks (GANs) have shown promising performance in generating realistic images. However, they often struggle in learning complex underlying modali…

cs.CV2018★ 4 cited

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

Hyojin Bahng, Seungjoo Yoo, Wonwoong Cho +4

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 generat…