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Junsoo Lee

8 accepted papers

2024

DreamStyler: Paint by Style Inversion with Text-to-Image Diffusion Models

AAAI 2024technical

Recent progresses in large-scale text-to-image models have yielded remarkable accomplishments, finding various applications in art domain. However, expressing unique characteristics of an artwork (e.g. brushwork, colortone, or composition) with text prompts alone may encounter limitations due to the…

2024

SAVE: Protagonist Diversification with Structure Agnostic Video Editing

ECCV 2024poster

"Driven by the upsurge progress in text-to-image (T2I) generation models, text-to-video (T2V) generation has experienced a significant advance as well. Accordingly, tasks such as modifying the object or changing the style in a video have been possible. However, previous works usually work well on tr…

2024

TCAN: Animating Human Images with Temporally Consistent Pose Guidance using Diffusion Models

ECCV 2024poster

"Pose-driven human-image animation diffusion models have shown remarkable capabilities in realistic human video synthesis. Despite the promising results achieved by previous approaches, challenges persist in achieving temporally consistent animation and ensuring robustness with off-the-shelf pose de…

2023

AesPA-Net: Aesthetic Pattern-Aware Style Transfer Networks

ICCV 2023poster

To deliver the artistic expression of the target style, recent studies exploit the attention mechanism owing to its ability to map the local patches of the style image to the corresponding patches of the content image. However, because of the low semantic correspondence between arbitrary content and…

Cited by 42PDFcodeScholar
2022

AnimeCeleb: Large-Scale Animation CelebHeads Dataset for Head Reenactment

ECCV 2022poster

"We present a novel Animation CelebHeads dataset (AnimeCeleb) to address an animation head reenactment. Different from previous animation head datasets, we utilize a 3D animation models as the controllable image samplers, which can provide a large amount of head images with their corresponding detai…

2021

Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation

AAAI 2021technical

Video generation models often operate under the assumption of fixed frame rates, which leads to suboptimal performance when it comes to handling flexible frame rates (e.g., increasing the frame rate of the more dynamic portion of the video as well as handling missing video frames). To resolve the re…

2020

Reference-Based Sketch Image Colorization Using Augmented-Self Reference and Dense Semantic Correspondence

CVPR 2020poster

This paper tackles the automatic colorization task of a sketch image given an already-colored reference image. Colorizing a sketch image is in high demand in comics, animation, and other content creation applications, but it suffers from information scarcity of a sketch image. To address this, a ref…

Cited by 382PDFScholar
2019

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

CVPR 2019poster

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 of training data. To tackle this issue, we present a novel memory-augmented colorization model MemoPainter that can produ…

Cited by 158PDFScholar