58 citations · 63 across the 6 of their papers we have counts for
7 papers
Fast 3D Foundation Model Initialized Gaussian Splatting
Anurag Dalal, Daniel Hagen, Kjell G. Robbersmyr +1
This paper introduces a fast method for high-quality 3D Gaussian Splatting (3DGS) reconstruction without traditional Structure-from-Motion (SfM). The proposed approach leverages 3D…
Gaussian Splatting: 3D Reconstruction and Novel View Synthesis, a Review
Anurag Dalal, Daniel Hagen, Kjell G. Robbersmyr +1
Image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of an object or scene from a set of input images. Learning-based methods have gained attent…
Loss- and Reward-Weighting for Efficient Distributed Reinforcement Learning
Martin Holen, Per-Arne Andersen, Kristian Muri Knausgård +1
This paper introduces two learning schemes for distributed agents in Reinforcement Learning (RL) environments, namely Reward-Weighted (R-Weighted) and Loss-Weighted (L-Weighted) gr…
A contrastive learning approach for individual re-identification in a wild fish population
Ørjan Langøy Olsen, Tonje Knutsen Sørdalen, Morten Goodwin +3
In both terrestrial and marine ecology, physical tagging is a frequently used method to study population dynamics and behavior. However, such tagging techniques are increasingly be…
Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook
Morten Goodwin, Kim Tallaksen Halvorsen, Lei Jiao +7
The deep learning revolution is touching all scientific disciplines and corners of our lives as a means of harnessing the power of big data. Marine ecology is no exception. These n…
Temperate Fish Detection and Classification: a Deep Learning based Approach
Kristian Muri Knausgård, Arne Wiklund, Tonje Knutsen Sørdalen +4
A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that c…