Monosdf: Exploring monocular geometric cues for neural implicit surface reconstruction
In recent years, neural implicit surface reconstruction methods have become popular for
multi-view 3D reconstruction. In contrast to traditional multi-view stereo methods, these …
multi-view 3D reconstruction. In contrast to traditional multi-view stereo methods, these …
Nerf-slam: Real-time dense monocular slam with neural radiance fields
We propose a novel geometric and photometric 3D map** pipeline for accurate and real-
time scene reconstruction from casually taken monocular images. To achieve this, we …
time scene reconstruction from casually taken monocular images. To achieve this, we …
Geowizard: Unleashing the diffusion priors for 3d geometry estimation from a single image
We introduce GeoWizard, a new generative foundation model designed for estimating
geometric attributes, eg, depth and normals, from single images. While significant research …
geometric attributes, eg, depth and normals, from single images. While significant research …
Mvdiffusion++: A dense high-resolution multi-view diffusion model for single or sparse-view 3d object reconstruction
This paper presents a neural architecture MVDiffusion++ for 3D object reconstruction that
synthesizes dense and high-resolution views of an object given one or a few images without …
synthesizes dense and high-resolution views of an object given one or a few images without …
Eslam: Efficient dense slam system based on hybrid representation of signed distance fields
We present ESLAM, an efficient implicit neural representation method for Simultaneous
Localization and Map** (SLAM). ESLAM reads RGB-D frames with unknown camera …
Localization and Map** (SLAM). ESLAM reads RGB-D frames with unknown camera …
[PDF][PDF] Deep review and analysis of recent nerfs
Neural radiance fields (NeRFs) refer to a suit of deep neural networks that are used to learn
and represent objects or scenes. Generally speaking, NeRFs have five main characters …
and represent objects or scenes. Generally speaking, NeRFs have five main characters …
Point-slam: Dense neural point cloud-based slam
We propose a dense neural simultaneous localization and map** (SLAM) approach for
monocular RGBD input which anchors the features of a neural scene representation in a …
monocular RGBD input which anchors the features of a neural scene representation in a …
Diffusionerf: Regularizing neural radiance fields with denoising diffusion models
Abstract Under good conditions, Neural Radiance Fields (NeRFs) have shown impressive
results on novel view synthesis tasks. NeRFs learn a scene's color and density fields by …
results on novel view synthesis tasks. NeRFs learn a scene's color and density fields by …
Nerf-det: Learning geometry-aware volumetric representation for multi-view 3d object detection
Abstract We present NeRF-Det, a novel method for indoor 3D detection with posed RGB
images as input. Unlike existing indoor 3D detection methods that struggle to model scene …
images as input. Unlike existing indoor 3D detection methods that struggle to model scene …
Benchmarking neural radiance fields for autonomous robots: An overview
Abstract Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …