36 citations · 47 across the 10 of their papers we have counts for
10 papers
Error-Conditioned Neural Solvers
Haina Jiang, Liam Wang, Peng-Chen Chen +4
Neural surrogate models offer fast approximate mappings from PDE parameters to solutions, but they typically treat solving as a purely statistical task: once trained, they struggle…
Projected Representation Conditioning for High-fidelity Novel View Synthesis
Min-Seop Kwak, Minkyung Kwon, Jinhyeok Choi +2
We propose a novel framework for diffusion-based novel view synthesis in which we leverage external representations as conditions, harnessing their geometric and semantic correspon…
CAMEO: Correspondence-Attention Alignment for Multi-View Diffusion Models
Minkyung Kwon, Jinhyeok Choi, Jiho Park +6
Multi-view diffusion models have recently emerged as a powerful paradigm for novel view synthesis, yet the underlying mechanism that enables their view-consistency remains unclear.…
Aligned Novel View Image and Geometry Synthesis via Cross-modal Attention Instillation
Min-Seop Kwak, Junho Kim, Sangdoo Yun +4
We introduce a diffusion-based framework that performs aligned novel view image and geometry generation via a warping-and-inpainting methodology. Unlike prior methods that require…
Geometry-Aware Score Distillation via 3D Consistent Noising and Gradient Consistency Modeling
Min-Seop Kwak, Donghoon Ahn, Ines Hyeonsu Kim +2
Score distillation sampling (SDS), the methodology in which the score from pretrained 2D diffusion models is distilled into 3D representation, has recently brought significant adva…
Retrieval-Augmented Score Distillation for Text-to-3D Generation
Junyoung Seo, Susung Hong, Wooseok Jang +4
Text-to-3D generation has achieved significant success by incorporating powerful 2D diffusion models, but insufficient 3D prior knowledge also leads to the inconsistency of 3D geom…
Self-Evolving Neural Radiance Fields
Jaewoo Jung, Jisang Han, Jiwon Kang +3
Recently, neural radiance field (NeRF) has shown remarkable performance in novel view synthesis and 3D reconstruction. However, it still requires abundant high-quality images, limi…
DaRF: Boosting Radiance Fields from Sparse Inputs with Monocular Depth Adaptation
Jiuhn Song, Seonghoon Park, Honggyu An +4
Neural radiance fields (NeRF) shows powerful performance in novel view synthesis and 3D geometry reconstruction, but it suffers from critical performance degradation when the numbe…
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…
GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency
Min-seop Kwak, Jiuhn Song, Seungryong Kim
We present a novel framework to regularize Neural Radiance Field (NeRF) in a few-shot setting with a geometry-aware consistency regularization. The proposed approach leverages a re…