5 citations · 20 across the 10 of their papers we have counts for
10 papers
AesPA-Net: Aesthetic Pattern-Aware Style Transfer Networks
Kibeom Hong, Seogkyu Jeon, Junsoo Lee +6
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 corre…
Chupa: Carving 3D Clothed Humans from Skinned Shape Priors using 2D Diffusion Probabilistic Models
Byungjun Kim, Patrick Kwon, Kwangho Lee +4
We propose a 3D generation pipeline that uses diffusion models to generate realistic human digital avatars. Due to the wide variety of human identities, poses, and stochastic detai…
Guiding Users to Where to Give Color Hints for Efficient Interactive Sketch Colorization via Unsupervised Region Prioritization
Youngin Cho, Junsoo Lee, Soyoung Yang +6
Existing deep interactive colorization models have focused on ways to utilize various types of interactions, such as point-wise color hints, scribbles, or natural-language texts, a…
Cross-Domain Style Mixing for Face Cartoonization
Seungkwon Kim, Chaeheon Gwak, Dohyun Kim +4
Cartoon domain has recently gained increasing popularity. Previous studies have attempted quality portrait stylization into the cartoon domain; however, this poses a great challeng…
Maximizing Cosine Similarity Between Spatial Features for Unsupervised Domain Adaptation in Semantic Segmentation
Inseop Chung, Daesik Kim, Nojun Kwak
We propose a novel method that tackles the problem of unsupervised domain adaptation for semantic segmentation by maximizing the cosine similarity between the source and the target…
Tell Me What They're Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction
Daesik Kim, Gyujeong Lee, Jisoo Jeong +1
In this work, we introduce a novel weakly supervised object detection (WSOD) paradigm to detect objects belonging to rare classes that have not many examples using transferable kno…
Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension
Daesik Kim, Seonhoon Kim, Nojun Kwak
In this work, we introduce a novel algorithm for solving the textbook question answering (TQA) task which describes more realistic QA problems compared to other recent tasks. We ma…
Vehicle Image Generation Going Well with The Surroundings
Jeesoo Kim, Jangho Kim, Jaeyoung Yoo +2
Since the generative neural networks have made a breakthrough in the image generation problem, lots of researches on their applications have been studied such as image restoration,…
Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams
Daesik Kim, Youngjoon Yoo, Jeesoo Kim +2
In this work, we introduce a new algorithm for analyzing a diagram, which contains visual and textual information in an abstract and integrated way. Whereas diagrams contain richer…
Where to Play: Retrieval of Video Segments using Natural-Language Queries
Sangkuk Lee, Daesik Kim, Myunggi Lee +2
In this paper, we propose a new approach for retrieval of video segments using natural language queries. Unlike most previous approaches such as concept-based methods or rule-based…