2.1k citations · 5.2k across the 53 of their papers we have counts for
6 papers · 1 filter
Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes
Alexandros Delitzas, Maria Parelli, Nikolas Hars +4
Training models to apply common-sense linguistic knowledge and visual concepts from 2D images to 3D scene understanding is a promising direction that researchers have only recently…
CLIP-Guided Vision-Language Pre-training for Question Answering in 3D Scenes
Maria Parelli, Alexandros Delitzas, Nikolas Hars +4
Training models to apply linguistic knowledge and visual concepts from 2D images to 3D world understanding is a promising direction that researchers have only recently started to e…
Mastering Spatial Graph Prediction of Road Networks
Sotiris Anagnostidis, Aurelien Lucchi, Thomas Hofmann
Accurately predicting road networks from satellite images requires a global understanding of the network topology. We propose to capture such high-level information by introducing…
OpenFilter: A Framework to Democratize Research Access to Social Media AR Filters
Piera Riccio, Bill Psomas, Francesco Galati +3
Augmented Reality or AR filters on selfies have become very popular on social media platforms for a variety of applications, including marketing, entertainment and aesthetics. Give…
Learning Aerial Image Segmentation from Online Maps
Pascal Kaiser, Jan Dirk Wegner, Aurelien Lucchi +3
This study deals with semantic segmentation of high-resolution (aerial) images where a semantic class label is assigned to each pixel via supervised classification as a basis for a…
A Semi-supervised Framework for Image Captioning
Wenhu Chen, Aurelien Lucchi, Thomas Hofmann
State-of-the-art approaches for image captioning require supervised training data consisting of captions with paired image data. These methods are typically unable to use unsupervi…