52 citations · 54 across the 3 of their papers we have counts for
4 papers · 1 filter
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
Nikhil Keetha, Norman Müller, Johannes Schönberger +14
We introduce MapAnything, a unified transformer-based feed-forward model that ingests one or more images along with optional geometric inputs such as camera intrinsics, poses, dept…
Disentangling Monocular 3D Object Detection
Andrea Simonelli, Samuel Rota Rota Bulò, Lorenzo Porzi +2
In this paper we propose an approach for monocular 3D object detection from a single RGB image, which leverages a novel disentangling transformation for 2D and 3D detection losses…
A Push-Pull Layer Improves Robustness of Convolutional Neural Networks
Nicola Strisciuglio, Manuel Lopez-Antequera, Nicolai Petkov
We propose a new layer in Convolutional Neural Networks (CNNs) to increase their robustness to several types of noise perturbations of the input images. We call this a push-pull la…
Training a Convolutional Neural Network for Appearance-Invariant Place Recognition
Ruben Gomez-Ojeda, Manuel Lopez-Antequera, Nicolai Petkov +1
Place recognition is one of the most challenging problems in computer vision, and has become a key part in mobile robotics and autonomous driving applications for performing loop c…