activity
20222026
most citedAE-NeRF: Auto-Encoding Neural Radiance Fields for 3D-Aware Object Manipulation

2 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2026★ 2 cited

RoomRecon: High-Quality Textured Room Layout Reconstruction on Mobile Devices

Seok Joon Kim, Dinh Duc Cao, Federica Spinola +2

Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmented reality (AR), virtual re…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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-…

cs.CV2022

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…

cs.CV2022★ 2 cited

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…