ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2408.08524
  4. Cited By
GS-ID: Illumination Decomposition on Gaussian Splatting via Diffusion
  Prior and Parametric Light Source Optimization

GS-ID: Illumination Decomposition on Gaussian Splatting via Diffusion Prior and Parametric Light Source Optimization

16 August 2024
Kang Du
Zhihao Liang
Zeyu Wang
    3DGS
ArXiv (abs)PDFHTML

Papers citing "GS-ID: Illumination Decomposition on Gaussian Splatting via Diffusion Prior and Parametric Light Source Optimization"

12 / 12 papers shown
Title
GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse Rendering
GI-GS: Global Illumination Decomposition on Gaussian Splatting for Inverse Rendering
Hongze Chen
Zehong Lin
Jun Zhang
3DGS
77
5
0
03 Oct 2024
2D Gaussian Splatting for Geometrically Accurate Radiance Fields
2D Gaussian Splatting for Geometrically Accurate Radiance Fields
Binbin Huang
Zehao Yu
Anpei Chen
Andreas Geiger
Shenghua Gao
3DGS
163
474
0
26 Mar 2024
IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering
  in Indoor Scenes
IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenes
Rui Zhu
Zhengqin Li
J. Matai
Fatih Porikli
Manmohan Chandraker
ViT
90
49
0
16 Jun 2022
Modeling Indirect Illumination for Inverse Rendering
Modeling Indirect Illumination for Inverse Rendering
Yuanqing Zhang
Jiaming Sun
Xingyi He He
Huan Fu
Rongfei Jia
Xiaowei Zhou
3DV
90
156
0
14 Apr 2022
Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision
  Datasets from 3D Scans
Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans
Ainaz Eftekhar
Alexander Sax
Roman Bachmann
Jitendra Malik
Amir Zamir
MedIm
88
299
0
11 Oct 2021
NeuS: Learning Neural Implicit Surfaces by Volume Rendering for
  Multi-view Reconstruction
NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction
Peng Wang
Lingjie Liu
Yuan Liu
Christian Theobalt
Taku Komura
Wenping Wang
99
1,728
0
20 Jun 2021
UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for
  Multi-View Reconstruction
UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction
Michael Oechsle
Songyou Peng
Andreas Geiger
108
751
0
20 Apr 2021
NeRV: Neural Reflectance and Visibility Fields for Relighting and View
  Synthesis
NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
Pratul P. Srinivasan
Boyang Deng
Xiuming Zhang
Matthew Tancik
B. Mildenhall
Jonathan T. Barron
80
604
0
07 Dec 2020
Neural Reflectance Fields for Appearance Acquisition
Neural Reflectance Fields for Appearance Acquisition
Sai Bi
Zexiang Xu
Pratul P. Srinivasan
B. Mildenhall
Kalyan Sunkavalli
Milovs Havsan
Yannick Hold-Geoffroy
D. Kriegman
R. Ramamoorthi
3DH
84
241
0
09 Aug 2020
Differentiable Volumetric Rendering: Learning Implicit 3D
  Representations without 3D Supervision
Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
Michael Niemeyer
L. Mescheder
Michael Oechsle
Andreas Geiger
3DH3DV
71
997
0
16 Dec 2019
DeepSDF: Learning Continuous Signed Distance Functions for Shape
  Representation
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Jeong Joon Park
Peter R. Florence
Julian Straub
Richard Newcombe
S. Lovegrove
3DV
131
3,688
0
16 Jan 2019
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
Eli Shechtman
Oliver Wang
EGVM
377
11,795
0
11 Jan 2018
1