Neural Radiance Field (NeRF), a new novel view synthesis with implicit scene
representation has taken the field of Computer Vision by storm. As a novel view synthesis …

Object pose detection and tracking has recently attracted increasing attention due to its wide
applications in many areas, such as autonomous driving, robotics, and augmented reality …

Abstract Recently 3D Gaussian Splatting has demonstrated impressive novel view synthesis
results reaching high fidelity and efficiency. However strong artifacts can be observed when …

Abstract We present Block-NeRF, a variant of Neural Radiance Fields that can represent
large-scale environments. Specifically, we demonstrate that when scaling NeRF to render …

Neural implicit representations have recently shown encouraging results in various
domains, including promising progress in simultaneous localization and mapping (SLAM) …

Abstract Training a Neural Radiance Field (NeRF) without pre-computed camera poses is
challenging. Recent advances in this direction demonstrate the possibility of jointly …

We present a super-fast convergence approach to reconstructing the per-scene radiance
field from a set of images that capture the scene with known poses. This task, which is often …

We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-
time scene reconstruction from casually taken monocular images. To achieve this, we …

A commonly observed failure mode of Neural Radiance Field (NeRF) is fitting incorrect
geometries when given an insufficient number of input views. One potential reason is that …

Recent advances in machine learning have led to increased interest in solving visual
computing problems using methods that employ coordinate‐based neural networks. These …