Search Results for author: Yeonjin Chang

Found 5 papers, 2 papers with code

HourglassNeRF: Casting an Hourglass as a Bundle of Rays for Few-shot Neural Rendering

no code implementations16 Mar 2024 Seunghyeon Seo, Yeonjin Chang, Jayeon Yoo, Seungwoo Lee, Hojun Lee, Nojun Kwak

Addressing this, we propose HourglassNeRF, an effective regularization-based approach with a novel hourglass casting strategy.

Neural Rendering Novel View Synthesis

Fast Sun-aligned Outdoor Scene Relighting based on TensoRF

no code implementations7 Nov 2023 Yeonjin Chang, Yearim Kim, Seunghyeon Seo, Jung Yi, Nojun Kwak

In this work, we introduce our method of outdoor scene relighting for Neural Radiance Fields (NeRF) named Sun-aligned Relighting TensoRF (SR-TensoRF).

FlipNeRF: Flipped Reflection Rays for Few-shot Novel View Synthesis

1 code implementation ICCV 2023 Seunghyeon Seo, Yeonjin Chang, Nojun Kwak

Neural Radiance Field (NeRF) has been a mainstream in novel view synthesis with its remarkable quality of rendered images and simple architecture.

Depth Estimation Novel View Synthesis

MixNeRF: Modeling a Ray with Mixture Density for Novel View Synthesis from Sparse Inputs

1 code implementation CVPR 2023 Seunghyeon Seo, Donghoon Han, Yeonjin Chang, Nojun Kwak

In this work, we propose MixNeRF, an effective training strategy for novel view synthesis from sparse inputs by modeling a ray with a mixture density model.

Depth Estimation Novel View Synthesis +1

Semantics-Guided Object Removal for Facial Images: with Broad Applicability and Robust Style Preservation

no code implementations29 Sep 2022 Jookyung Song, Yeonjin Chang, SeongUk Park, Nojun Kwak

U-net, a conventional approach for conditional GANs, retains fine details of unmasked regions but the style of the reconstructed image is inconsistent with the rest of the original image and only works robustly when the size of the occluding object is small enough.

Image Inpainting

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