313 citations · 376 across the 17 of their papers we have counts for
7 papers · 1 filter
User-friendly Image Editing with Minimal Text Input: Leveraging Captioning and Injection Techniques
Sunwoo Kim, Wooseok Jang, Hyunsu Kim +4
Recent text-driven image editing in diffusion models has shown remarkable success. However, the existing methods assume that the user's description sufficiently grounds the context…
Diffusion Model for Dense Matching
Jisu Nam, Gyuseong Lee, Sunwoo Kim +4
The objective for establishing dense correspondence between paired images consists of two terms: a data term and a prior term. While conventional techniques focused on defining han…
Semantic-Preserving Augmentation for Robust Image-Text Retrieval
Sunwoo Kim, Kyuhong Shim, Luong Trung Nguyen +1
Image text retrieval is a task to search for the proper textual descriptions of the visual world and vice versa. One challenge of this task is the vulnerability to input image and…
Controllable Style Transfer via Test-time Training of Implicit Neural Representation
Sunwoo Kim, Youngjo Min, Younghun Jung +1
We propose a controllable style transfer framework based on Implicit Neural Representation that pixel-wisely controls the stylized output via test-time training. Unlike traditional…
REVECA -- Rich Encoder-decoder framework for Video Event CAptioner
Jaehyuk Heo, YongGi Jeong, Sunwoo Kim +2
We describe an approach used in the Generic Boundary Event Captioning challenge at the Long-Form Video Understanding Workshop held at CVPR 2022. We designed a Rich Encoder-decoder…
Deep Translation Prior: Test-time Training for Photorealistic Style Transfer
Sunwoo Kim, Soohyun Kim, Seungryong Kim
Recent techniques to solve photorealistic style transfer within deep convolutional neural networks (CNNs) generally require intensive training from large-scale datasets, thus havin…
Online Exemplar Fine-Tuning for Image-to-Image Translation
Taewon Kang, Soohyun Kim, Sunwoo Kim +1
Existing techniques to solve exemplar-based image-to-image translation within deep convolutional neural networks (CNNs) generally require a training phase to optimize the network p…