activity
20202024
most citedDeep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings

4 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

physics.optics2024

Optical Diffusion Models for Image Generation

Ilker Oguz, Niyazi Ulas Dinc, Mustafa Yildirim +6

Diffusion models generate new samples by progressively decreasing the noise from the initially provided random distribution. This inference procedure generally utilizes a trained n…

cs.CV2024

Parrot: Pareto-optimal Multi-Reward Reinforcement Learning Framework for Text-to-Image Generation

Seung Hyun Lee, Yinxiao Li, Junjie Ke +11

Recent works have demonstrated that using reinforcement learning (RL) with multiple quality rewards can improve the quality of generated images in text-to-image (T2I) generation. H…

cs.CV2023★ 3 cited

Soundini: Sound-Guided Diffusion for Natural Video Editing

Seung Hyun Lee, Sieun Kim, Innfarn Yoo +6

We propose a method for adding sound-guided visual effects to specific regions of videos with a zero-shot setting. Animating the appearance of the visual effect is challenging beca…

cs.CV2021★ 4 cited

Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings

Innfarn Yoo, Huiwen Chang, Xiyang Luo +4

Digital watermarking is widely used for copyright protection. Traditional 3D watermarking approaches or commercial software are typically designed to embed messages into 3D meshes,…

eess.IV2020

GIFnets: Differentiable GIF Encoding Framework

Innfarn Yoo, Xiyang Luo, Yilin Wang +2

Graphics Interchange Format (GIF) is a widely used image file format. Due to the limited number of palette colors, GIF encoding often introduces color banding artifacts. Traditiona…