Fetching the paper…
Reading the bibliography…
Neural Radiance Fields (NeRFs) have achieved impressive results in novel view synthesis and surface reconstruction tasks.
Distinctive image features from scale-invariant keypoints
David G. Lowe · 2004
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, and Eero P. Simoncelli · 2004
Earlier work this paper cites.
Histograms of oriented gradients for human detection
Navneet Dalal and Bill Triggs · 2005
Earlier work this paper cites.
SURF: speeded up robust features
Herbert Bay, Tinne Tuytelaars, and Luc Van Gool · 2006
Earlier work this paper cites.
Large scale multi-view stereopsis evaluation
Rasmus Ramsbøl Jensen, Anders Lindbjerg Dahl, George Vogiatzis, Engin Tola, and Henrik Aanæs · 2014
Earlier work this paper cites.
Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
Earlier work this paper cites.
LIFT: learned invariant feature transform
Kwang Moo Yi, Eduard Trulls, Vincent Lepetit, and Pascal Fua · 2016
Earlier work this paper cites.
ScanNet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas A. Funkhouser, and Matthias Nießner · 2017
Earlier work this paper cites.
Superpoint: Self-supervised interest point detection and description
Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2018
Earlier work this paper cites.
MegaDepth: Learning single-view depth prediction from internet photos
Zhengqi Li and Noah Snavely · 2018
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Earlier work this paper cites.
Occupancy networks: Learning 3d reconstruction in function space
Lars M. Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Earlier work this paper cites.
DeepSDF: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard A. Newcombe, and Steven Lovegrove · 2019
Earlier work this paper cites.
View independent generative adversarial network for novel view synthesis
Xiaogang Xu, Ying-Cong Chen, and Jiaya Jia · 2019
Earlier work this paper cites.
Local light field fusion: practical view synthesis with prescriptive sampling guidelines
Ben Mildenhall, Pratul P. Srinivasan, Rodrigo Ortiz Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar · 2019
Earlier work this paper cites.
Neural-guided RANSAC: learning where to sample model hypotheses
Eric Brachmann and Carsten Rother · 2019
Earlier work this paper cites.
Dgc-net: Dense geometric correspondence network
Iaroslav Melekhov, Aleksei Tiulpin, Torsten Sattler, Marc Pollefeys, Esa Rahtu, and Juho Kannala · 2019
Earlier work this paper cites.
NeRF: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng · 2020
Cited alongside, same era.
Deep 3d portrait from a single image
Sicheng Xu, Jiaolong Yang, Dong Chen, Fang Wen, Yu Deng, Yunde Jia, and Xin Tong · 2020
Cited alongside, same era.
NeRF++: Analyzing and improving neural radiance fields
Kai Zhang, Gernot Riegler, Noah Snavely, and Vladlen Koltun · 2020
Cited alongside, same era.
superglue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
Cited alongside, same era.
Glu-net: Global-local universal network for dense flow and correspondences
Prune Truong, Martin Danelljan, and Radu Timofte · 2020
Cited alongside, same era.
Template nerf: Towards modeling dense shape correspondences from category-specific object images
Jianfei Guo, Zhiyuan Yang, Xi Lin, and Qingfu Zhang · 2021
Later among the works it cites.
Smartportraits: Depth powered handheld smartphone dataset of human portraits for state estimation, reconstruction and synthesis
Anastasiia Kornilova, Marsel Faizullin, Konstantin Pakulev, Andrey Sadkov, Denis Kukushkin, Azat Akhmetyanov, Timur Akhtyamov, Hekmat Taherinejad, and Gonzalo Ferrer · 2022
Later among the works it cites.
Block-nerf: Scalable large scene neural view synthesis
Matthew Tancik, Vincent Casser, Xinchen Yan, Sabeek Pradhan, Ben P. Mildenhall, Pratul P. Srinivasan, Jonathan T. Barron, and Henrik Kretzschmar · 2022
Later among the works it cites.
Mega-nerf: Scalable construction of large-scale nerfs for virtual fly-throughs
Haithem Turki, Deva Ramanan, and Mahadev Satyanarayanan · 2022
Later among the works it cites.
Depth-supervised nerf: Fewer views and faster training for free
Kangle Deng, Andrew Liu, Jun-Yan Zhu, and Deva Ramanan · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Lior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Ronen Basri, and Yaron Lipman · 2020
Cited alongside, same era.
Nerf in the wild: Neural radiance fields for unconstrained photo collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi S. M. Sajjadi, Jonathan T. Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
Cited alongside, same era.
pixelNeRF: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
Cited alongside, same era.
Putting nerf on a diet: Semantically consistent few-shot view synthesis
Ajay Jain, Matthew Tancik, and Pieter Abbeel · 2021
Cited alongside, same era.
UNISURF: unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
Cited alongside, same era.
NeuS: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
Peng Wang, Lingjie Liu, Yuan Liu, Christian Theobalt, Taku Komura, and Wenping Wang · 2021
Cited alongside, same era.
Loftr: Detector-free local feature matching with transformers
Jiaming Sun, Zehong Shen, Yuang Wang, Hujun Bao, and Xiaowei Zhou · 2021
Cited alongside, same era.
Later among the works it cites.
Dense depth priors for neural radiance fields from sparse input views
Barbara Roessle, Jonathan T. Barron, Ben Mildenhall, Pratul P. Srinivasan, and Matthias Nießner · 2022
Later among the works it cites.
InfoNeRF: Ray entropy minimization for few-shot neural volume rendering
Mijeong Kim, Seonguk Seo, and Bohyung Han · 2022
Later among the works it cites.
MonoSDF: Exploring monocular geometric cues for neural implicit surface reconstruction
Zehao Yu, Songyou Peng, Michael Niemeyer, Torsten Sattler, and Andreas Geiger · 2022
Later among the works it cites.
Neuris: Neural reconstruction of indoor scenes using normal priors
Jiepeng Wang, Peng Wang, Xiaoxiao Long, Christian Theobalt, Taku Komura, Lingjie Liu, and Wenping Wang · 2022
Later among the works it cites.
Dkm: Dense kernelized feature matching for geometry estimation
Johan Edstedt, Ioannis Athanasiadis, Mårten Wadenbäck, and Michael Felsberg · 2022
Later among the works it cites.
Ray priors through reprojection: Improving neural radiance fields for novel view extrapolation
Jian Zhang, Yuanqing Zhang, Huan Fu, Xiaowei Zhou, Bowen Cai, Jinchi Huang, Rongfei Jia, Binqiang Zhao, and Xing Tang · 2022
Later among the works it cites.
RegNeRF: Regularizing neural radiance fields for view synthesis from sparse inputs
Michael Niemeyer, Jonathan T. Barron, Ben Mildenhall, Mehdi S. M. Sajjadi, Andreas Geiger, and Noha Radwan · 2022
Later among the works it cites.
Neural 3d scene reconstruction with the manhattan-world assumption
Haoyu Guo, Sida Peng, Haotong Lin, Qianqian Wang, Guofeng Zhang, Hujun Bao, and Xiaowei Zhou · 2022
Later among the works it cites.
Quadtree attention for vision transformers
Shitao Tang, Jiahui Zhang, Siyu Zhu, and Ping Tan · 2022
Later among the works it cites.
Matchformer: Interleaving attention in transformers for feature matching
Qing Wang, Jiaming Zhang, Kailun Yang, Kunyu Peng, and Rainer Stiefelhagen · 2022
Later among the works it cites.
Nerf-supervision: Learning dense object descriptors from neural radiance fields
Lin Yen-Chen, Pete Florence, Jonathan T Barron, Tsung-Yi Lin, Alberto Rodriguez, and Phillip Isola · 2022
Later among the works it cites.
ConsistentNeRF: Enhancing neural radiance fields with 3d consistency for sparse view synthesis
Shoukang Hu, Kaichen Zhou, Kaiyu Li, Longhui Yu, Lanqing Hong, Tianyang Hu, Zhenguo Li, Gim Hee Lee, and Ziwei Liu · 2023
Closest in time.
SPARF: neural radiance fields from sparse and noisy poses
Prune Truong, Marie-Julie Rakotosaona, Fabian Manhardt, and Federico Tombari · 2023
Closest in time.