activity
20232026
most citedText2Control3D: Controllable 3D Avatar Generation in Neural Radiance Fields using Geometry-Guided Text-to-Image Diffusion Model

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

collaborators

6 papers

cs.RO2026

An Agentic Framework for Proactive Robots with Procedural Assistance Memory

Dohyun Lee, Minho Park, Jeonghoon Park +5

Proactive robots should anticipate user needs and provide assistance before being explicitly asked. A straightforward approach is to infer human intentions from commonsense knowled…

cs.CV2025

SphereDiff: Tuning-free 360° Static and Dynamic Panorama Generation via Spherical Latent Representation

Minho Park, Taewoong Kang, Jooyeol Yun +2

The increasing demand for AR/VR applications has highlighted the need for high-quality content, such as 360° live wallpapers. However, generating high-quality 360° panoramic conten…

cs.GR2024★ 1 cited

SurFhead: Affine Rig Blending for Geometrically Accurate 2D Gaussian Surfel Head Avatars

Jaeseong Lee, Taewoong Kang, Marcel C. Bühler +5

Recent advancements in head avatar rendering using Gaussian primitives have achieved significantly high-fidelity results. Although precise head geometry is crucial for applications…

cs.CV2024★ 1 cited

VEGS: View Extrapolation of Urban Scenes in 3D Gaussian Splatting using Learned Priors

Sungwon Hwang, Min-Jung Kim, Taewoong Kang +2

Neural rendering-based urban scene reconstruction methods commonly rely on images collected from driving vehicles with cameras facing and moving forward. Although these methods can…

cs.CV2024

Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting

Junha Hyung, Susung Hong, Sungwon Hwang +3

3D reconstruction from multi-view images is one of the fundamental challenges in computer vision and graphics. Recently, 3D Gaussian Splatting (3DGS) has emerged as a promising tec…

cs.CV2023★ 2 cited

Text2Control3D: Controllable 3D Avatar Generation in Neural Radiance Fields using Geometry-Guided Text-to-Image Diffusion Model

Sungwon Hwang, Junha Hyung, Jaegul Choo

Recent advances in diffusion models such as ControlNet have enabled geometrically controllable, high-fidelity text-to-image generation. However, none of them addresses the question…