BLOG
Opinions, experiments and reality from inside the lab
Our scientists share their knowledge and perpectives across the different fields of work and emerging trends in spatial AI, robotics, computer vision, NLP, machine learning and human-robot interaction. These articles explain our research lines and future directions without the need for deep technical knowledge.
2 December 2021
Theoretical and experimental findings to improve regression applications: a 3D rotation case study. Code.
2021
29 November 2021
A novel, plug and play model for human 3D shape estimation of the body or hands, in videos which is trained by mimicking the BERT algorithm from the natural language processing community.
2021
21 June 2021
Using domain randomization and meta-learning, computer vision models forget less when exposed to training samples from new domains. Remembering is a crucial element in the deployment of self-driving cars and robots which interact in dynamic environments.
2021
19 May 2021
NAVER LABS releases world's biggest visual localization dataset of indoor spaces with over 130K images. Dataset built with NAVER LABS mapping robots M1X & COMET and available in unified data format kapture.
2021
31 March 2021
Visual localization is used by robots and self-driving cars to estimate their position and in AR apps to interact with the physical world both indoors and out in the open. This article gives an overview of current state-of-the-art methods and their advantages and drawbacks.
2021
8 December 2020
How harder negatives facilitate better and faster contrastive self-supervised learning and ways of synthesizing harder negative features on-the-fly.
2020
24 August 2020
How mid-size sets of captioned images can rival with large-scale labelled image sets to learn generic representations
2020
12 June 2020
A first-of-its-kind architecture that, based on a single image, predicts how a robot can pick up objects from within any scene could revolutionize applications in AR/VR and robotics.
2020
29 January 2020
Latest release of the popular synthetic image dataset for training and testing. New features include increased photorealism, stereo cameras and additional ground truth.
2020
4 December 2019
Combining keypoint reliability in an image as part of the keypoint detection problem significantly improves feature matching.
2019
25 October 2019
Evaluating our method on public datasets, we show that it can successfully solve challenging situations in dynamic environments which cause state-of-the-art baseline VSLAM algorithms to fail and that it maintains performance on static scenes.
2019
18 October 2019
Fine-grained action retrieval made possible thanks to a new annotated dataset and part-of-speech embedding.
2019