Finding local features that are repeatable across multiple views is a cornerstone of sparse
3D reconstruction. The classical image matching paradigm detects keypoints per-image …

Image descriptors based on activations of Convolutional Neural Networks (CNNs) have
become dominant in image retrieval due to their discriminative power, compactness of …

This work presents a Multi-View Stereo system for robust and efficient dense modeling from
unstructured image collections. Our core contributions are the joint estimation of depth and …

Visual localization enables autonomous vehicles to navigate in their surroundings and
augmented reality applications to link virtual to real worlds. Practical visual localization …

Abstract Incremental Structure-from-Motion is a prevalent strategy for 3D reconstruction from
unordered image collections. While incremental reconstruction systems have tremendously …

Low-light image enhancement is challenging in that it needs to consider not only brightness
recovery but also complex issues like color distortion and noise, which usually hide in the …

In this paper we address issues with image retrieval benchmarking on standard and popular
Oxford 5k and Paris 6k datasets. In particular, annotation errors, the size of the dataset, and …

Abstract Neural Radiance Fields (NeRF) has recently gained popularity for its impressive
novel view synthesis ability. This paper studies the problem of hallucinated NeRF: ie …

Visual localization enables autonomous vehicles to navigate in their surroundings and
augmented reality applications to link virtual to real worlds. Practical visual localization …

Abstract Convolutional Neural Networks (CNNs) achieve state-of-the-art performance in
many computer vision tasks. However, this achievement is preceded by extreme manual …