In recent years a vast amount of visual content has been generated and shared from many
fields, such as social media platforms, medical imaging, and robotics. This abundance of …

With the development of Internet technology and the popularity of digital devices, Content-
Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …

The recent breakthroughs in natural language processing for model pretraining on large
quantities of data have opened the way for similar foundation models in computer vision …

In this paper, we question if self-supervised learning provides new properties to Vision
Transformer (ViT) that stand out compared to convolutional networks (convnets). Beyond the …

Abstract Visual Place Recognition is a challenging task for robotics and autonomous
systems, which must deal with the twin problems of appearance and viewpoint change in an …

Interest point detection and local feature description are fundamental steps in many
computer vision applications. Classical approaches are based on a detect-then-describe …

The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …

Multi-view stereo reconstruction (MVS) in the wild requires to first estimate the camera
intrinsic and extrinsic parameters. These are usually tedious and cumbersome to obtain yet …

Image retrieval is the problem of searching an image database for items that are similar to a
query image. To address this task, two main types of image representations have been …

While image retrieval and instance recognition techniques are progressing rapidly, there is a
need for challenging datasets to accurately measure their performance--while posing novel …