7 citations · 21 across the 7 of their papers we have counts for
7 papers
Sign Language Translation from Instructional Videos
Laia Tarrés, Gerard I. Gállego, Amanda Duarte +2
The advances in automatic sign language translation (SLT) to spoken languages have been mostly benchmarked with datasets of limited size and restricted domains. Our work advances t…
Model Zoos: A Dataset of Diverse Populations of Neural Network Models
Konstantin Schürholt, Diyar Taskiran, Boris Knyazev +2
In the last years, neural networks (NN) have evolved from laboratory environments to the state-of-the-art for many real-world problems. It was shown that NN models (i.e., their wei…
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights
Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto +1
Learning representations of neural network weights given a model zoo is an emerging and challenging area with many potential applications from model inspection, to neural architect…
Hyper-Representations for Pre-Training and Transfer Learning
Konstantin Schürholt, Boris Knyazev, Xavier Giró-i-Nieto +1
Learning representations of neural network weights given a model zoo is an emerging and challenging area with many potential applications from model inspection, to neural architect…
Sign Language Video Retrieval with Free-Form Textual Queries
Amanda Duarte, Samuel Albanie, Xavier Giró-i-Nieto +1
Systems that can efficiently search collections of sign language videos have been highlighted as a useful application of sign language technology. However, the problem of searching…
Multiple Object Tracking with Mixture Density Networks for Trajectory Estimation
Andreu Girbau, Xavier Giró-i-Nieto, Ignasi Rius +1
Multiple object tracking faces several challenges that may be alleviated with trajectory information. Knowing the posterior locations of an object helps disambiguating and solving…
Curriculum Learning for Recurrent Video Object Segmentation
Maria Gonzalez-i-Calabuig, Carles Ventura, Xavier Giró-i-Nieto
Video object segmentation can be understood as a sequence-to-sequence task that can benefit from the curriculum learning strategies for better and faster training of deep neural ne…