1 citations · 1 across the 5 of their papers we have counts for
5 papers
HuRo: Robotizing Human Videos for Scalable VLA Pretraining
Jinho Jeong, Se June Joo, Jaehyun Kang +4
Human video datasets offer an abundant and diverse source of interaction data that can complement expensive real-robot data. To bridge the human-to-robot embodiment gap, existing a…
APT: Improving Diffusion Models for High Resolution Image Generation with Adaptive Path Tracing
Sangmin Han, Jinho Jeong, Jinwoo Kim +1
Latent Diffusion Models (LDMs) are generally trained at fixed resolutions, limiting their capability when scaling up to high-resolution images. While training-based approaches addr…
ORIDa: Object-centric Real-world Image Composition Dataset
Jinwoo Kim, Sangmin Han, Jinho Jeong +3
Object compositing, the task of placing and harmonizing objects in images of diverse visual scenes, has become an important task in computer vision with the rise of generative mode…
Latent Space Super-Resolution for Higher-Resolution Image Generation with Diffusion Models
Jinho Jeong, Sangmin Han, Jinwoo Kim +1
In this paper, we propose LSRNA, a novel framework for higher-resolution (exceeding 1K) image generation using diffusion models by leveraging super-resolution directly in the laten…
Accelerating Image Super-Resolution Networks with Pixel-Level Classification
Jinho Jeong, Jinwoo Kim, Younghyun Jo +1
In recent times, the need for effective super-resolution (SR) techniques has surged, especially for large-scale images ranging 2K to 8K resolutions. For DNN-based SISR, decomposing…