Mvimgnet: A large-scale dataset of multi-view images
Being data-driven is one of the most iconic properties of deep learning algorithms. The birth
of ImageNet drives a remarkable trend of" learning from large-scale data" in computer vision …
of ImageNet drives a remarkable trend of" learning from large-scale data" in computer vision …
Go-slam: Global optimization for consistent 3d instant reconstruction
Neural implicit representations have recently demonstrated compelling results on dense
Simultaneous Localization And Mapping (SLAM) but suffer from the accumulation of errors …
Simultaneous Localization And Mapping (SLAM) but suffer from the accumulation of errors …
Image-based 3D reconstruction for Multi-Scale civil and infrastructure Projects: A review from 2012 to 2022 with new perspective from deep learning methods
As a bridge between physical objects and as-built models, image-based 3D reconstruction
performs a vital role by generating point cloud models, mesh models, textured models, and …
performs a vital role by generating point cloud models, mesh models, textured models, and …
Scade: Nerfs from space carving with ambiguity-aware depth estimates
MA Uy, R Martin-Brualla… - Proceedings of the …, 2023 - openaccess.thecvf.com
Neural radiance fields (NeRFs) have enabled high fidelity 3D reconstruction from multiple
2D input views. However, a well-known drawback of NeRFs is the less-than-ideal …
2D input views. However, a well-known drawback of NeRFs is the less-than-ideal …
Cl-MVSNet: Unsupervised multi-view stereo with dual-level contrastive learning
Abstract Unsupervised Multi-View Stereo (MVS) methods have achieved promising progress
recently. However, previous methods primarily depend on the photometric consistency …
recently. However, previous methods primarily depend on the photometric consistency …
Single drone-based 3D reconstruction approach to improve public engagement in conservation of heritage buildings: A case of Hakka Tulou
Public engagement in protecting architectural heritage is a critical component of sustainable
development. This study has developed an innovative single drone-based 3D reconstruction …
development. This study has developed an innovative single drone-based 3D reconstruction …
Geometry-aware Reconstruction and Fusion-refined Rendering for Generalizable Neural Radiance Fields
Generalizable NeRF aims to synthesize novel views for unseen scenes. Common practices
involve constructing variance-based cost volumes for geometry reconstruction and encoding …
involve constructing variance-based cost volumes for geometry reconstruction and encoding …
Large-scale aerial scene perception based on self-supervised multi-view stereo via cycled generative adversarial network
KW Tong, Z Shi, GY Zhu, Y Duan, Y Hou, EQ Wu… - Information …, 2024 - Elsevier
Unmanned aerial vehicle (UAV) has the characteristics of strong maneuverability and wide
field of vision, and its application in real-time terrain perception and target capture is one of …
field of vision, and its application in real-time terrain perception and target capture is one of …
GSNeRF: Generalizable Semantic Neural Radiance Fields with Enhanced 3D Scene Understanding
Utilizing multi-view inputs to synthesize novel-view images Neural Radiance Fields (NeRF)
have emerged as a popular research topic in 3D vision. In this work we introduce a …
have emerged as a popular research topic in 3D vision. In this work we introduce a …
C2f2neus: Cascade cost frustum fusion for high fidelity and generalizable neural surface reconstruction
There is an emerging effort to combine the two popular 3D frameworks using Multi-View
Stereo (MVS) and Neural Implicit Surfaces (NIS) with a specific focus on the few-shot/sparse …
Stereo (MVS) and Neural Implicit Surfaces (NIS) with a specific focus on the few-shot/sparse …