HyperAI
HyperAI초신경
홈
뉴스
최신 연구 논문
튜토리얼
데이터셋
백과사전
SOTA
LLM 모델
GPU 랭킹
컨퍼런스
전체 검색
소개
한국어
HyperAI
HyperAI초신경
Toggle sidebar
전체 사이트 검색...
⌘
K
홈
SOTA
새로운 시점 합성
Novel View Synthesis On Nerf
Novel View Synthesis On Nerf
평가 지표
LPIPS
PSNR
SSIM
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
LPIPS
PSNR
SSIM
Paper Title
Repository
JAXNeRF
0.051
31.65
0.952
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
-
Plenoxels
-
31.71
0.958
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance
-
K-Planes (hybrid)
-
32.36
0.967
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance
-
PVD_Hash2NeRF
-
-
-
One is All: Bridging the Gap Between Neural Radiance Fields Architectures with Progressive Volume Distillation
-
I-NGP
-
33.18
-
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance
-
K-Planes (explicit)
-
32.21
0.964
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance
-
Deformable Beta Splatting
0.028
34.66
0.973
Deformable Beta Splatting
-
TensoRF
-
33.14
0.963
K-Planes: Explicit Radiance Fields in Space, Time, and Appearance
-
NeRF
0.081
31
0.947
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
-
MobileNeRF
0.062
30.9
0.947
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
-
Self-Organizing Gaussians
0.031
33.7
0.969
Compact 3D Scene Representation via Self-Organizing Gaussian Grids
-
SNeRG
0.05
30.38
0.95
MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures
-
0 of 12 row(s) selected.
Previous
Next
Novel View Synthesis On Nerf | SOTA | HyperAI초신경