1 code implementation • 30 Jul 2021 • Hassan Hayat, Carles Ventura, Agata Lapedriza
In this paper, we model the emotions evoked by videos in a different manner: instead of modeling the aggregated value we jointly model the emotions experienced by each viewer and the aggregated value using a multi-task learning approach.
2 code implementations • 8 Jun 2021 • Ioannis Kazakos, Carles Ventura, Miriam Bellver, Carina Silberer, Xavier Giro-i-Nieto
Recent advances in deep learning have brought significant progress in visual grounding tasks such as language-guided video object segmentation.
2 code implementations • 1 Oct 2020 • Miriam Bellver, Carles Ventura, Carina Silberer, Ioannis Kazakos, Jordi Torres, Xavier Giro-i-Nieto
The task of video object segmentation with referring expressions (language-guided VOS) is to, given a linguistic phrase and a video, generate binary masks for the object to which the phrase refers.
Ranked #1 on Referring Expression Segmentation on A2Dre test
1 code implementation • 15 Aug 2020 • 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 networks.
no code implementations • 5 Nov 2019 • Alba Herrera-Palacio, Carles Ventura, Carina Silberer, Ionut-Teodor Sorodoc, Gemma Boleda, Xavier Giro-i-Nieto
The goal of this work is to segment the objects in an image that are referred to by a sequence of linguistic descriptions (referring expressions).
1 code implementation • CVPR 2019 • Carles Ventura, Miriam Bellver, Andreu Girbau, Amaia Salvador, Ferran Marques, Xavier Giro-i-Nieto
Multiple object video object segmentation is a challenging task, specially for the zero-shot case, when no object mask is given at the initial frame and the model has to find the objects to be segmented along the sequence.
Ranked #1 on One-shot visual object segmentation on YouTube-VOS
1 code implementation • 28 Aug 2018 • Carles Ventura, Jordi Pont-Tuset, Sergi Caelles, Kevis-Kokitsi Maninis, Luc van Gool
This paper tackles the task of estimating the topology of road networks from aerial images.
no code implementations • 4 Dec 2017 • Carles Ventura, Jordi Pont-Tuset, Sergi Caelles, Kevis-Kokitsi Maninis, Luc van Gool
This paper tackles the task of estimating the topology of filamentary networks such as retinal vessels and road networks.
no code implementations • 27 May 2015 • Carles Ventura, Xavier Giró-i-Nieto, Verónica Vilaplana, Kevin McGuinness, Ferran Marqués, Noel E. O'Connor
This paper explores novel approaches for improving the spatial codification for the pooling of local descriptors to solve the semantic segmentation problem.