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Found 11 papers, 7 papers with code
Collaborative Visual Place Recognition through Federated Learning
Visual Place Recognition (VPR) aims to estimate the location of an image by treating it as a retrieval problem.
What does CLIP know about peeling a banana?
Humans show an innate capability to identify tools to support specific actions.
The Unreasonable Effectiveness of Pre-Trained Features for Camera Pose Refinement
This involves training an implicit scene representation or learning features while optimizing a camera pose-based loss.
JIST: Joint Image and Sequence Training for Sequential Visual Place Recognition
As a mitigation to this problem, we propose a novel Joint Image and Sequence Training protocol (JIST) that leverages large uncurated sets of images through a multi-task learning framework.
EigenPlaces: Training Viewpoint Robust Models for Visual Place Recognition
Visual Place Recognition is a task that aims to predict the place of an image (called query) based solely on its visual features.
Ranked #1 on
Visual Place Recognition
on SF-XL test v1
Divide&Classify: Fine-Grained Classification for City-Wide Visual Place Recognition
Our method, Divide&Classify (D&C), enjoys the fast inference of classification solutions and an accuracy competitive with retrieval methods on the fine-grained, city-wide setting.
Are Local Features All You Need for Cross-Domain Visual Place Recognition?
Despite recent advances, recognizing the same place when the query comes from a significantly different distribution is still a major hurdle for state of the art retrieval methods.
Divide&Classify: Fine-Grained Classification for City-Wide Visual Geo-Localization
In this paper we investigate whether we can effectively approach this task as a classification problem, thus bypassing the need for a similarity search.
PoliTO-IIT-CINI Submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition
In this report, we describe the technical details of our submission to the EPIC-Kitchens-100 Unsupervised Domain Adaptation (UDA) Challenge in Action Recognition.
Learning Sequential Descriptors for Sequence-based Visual Place Recognition
In robotics, Visual Place Recognition is a continuous process that receives as input a video stream to produce a hypothesis of the robot's current position within a map of known places.
Deep Visual Geo-localization Benchmark
In this paper, we propose a new open-source benchmarking framework for Visual Geo-localization (VG) that allows to build, train, and test a wide range of commonly used architectures, with the flexibility to change individual components of a geo-localization pipeline.
