36 citations · 40 across the 5 of their papers we have counts for
5 papers
GaussianTalker: Real-Time High-Fidelity Talking Head Synthesis with Audio-Driven 3D Gaussian Splatting
Kyusun Cho, Joungbin Lee, Heeji Yoon +4
We propose GaussianTalker, a novel framework for real-time generation of pose-controllable talking heads. It leverages the fast rendering capabilities of 3D Gaussian Splatting (3DG…
Talk3D: High-Fidelity Talking Portrait Synthesis via Personalized 3D Generative Prior
Jaehoon Ko, Kyusun Cho, Joungbin Lee +4
Recent methods for audio-driven talking head synthesis often optimize neural radiance fields (NeRF) on a monocular talking portrait video, leveraging its capability to render high-…
Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation
Junyoung Seo, Wooseok Jang, Min-Seop Kwak +6
Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neura…
3D GAN Inversion with Pose Optimization
Jaehoon Ko, Kyusun Cho, Daewon Choi +2
With the recent advances in NeRF-based 3D aware GANs quality, projecting an image into the latent space of these 3D-aware GANs has a natural advantage over 2D GAN inversion: not on…
AE-NeRF: Auto-Encoding Neural Radiance Fields for 3D-Aware Object Manipulation
Mira Kim, Jaehoon Ko, Kyusun Cho +3
We propose a novel framework for 3D-aware object manipulation, called Auto-Encoding Neural Radiance Fields (AE-NeRF). Our model, which is formulated in an auto-encoder architecture…