Zobrazeno 1 - 10
of 9 577
pro vyhledávání: '"João F"'
Autor:
Sun, Xingzhi, Xu, Charles, Rocha, João F., Liu, Chen, Hollander-Bodie, Benjamin, Goldman, Laney, DiStasio, Marcello, Perlmutter, Michael, Krishnaswamy, Smita
In many data-driven applications, higher-order relationships among multiple objects are essential in capturing complex interactions. Hypergraphs, which generalize graphs by allowing edges to connect any number of nodes, provide a flexible and powerfu
Externí odkaz:
http://arxiv.org/abs/2409.09469
Reconstructing realistic 3D human models from monocular images has significant applications in creative industries, human-computer interfaces, and healthcare. We base our work on 3D Gaussian Splatting (3DGS), a scene representation composed of a mixt
Externí odkaz:
http://arxiv.org/abs/2409.04196
Recent advancements in machine learning have fueled research on multimodal tasks, such as for instance text-to-video and text-to-audio retrieval. These tasks require models to understand the semantic content of video and audio data, including objects
Externí odkaz:
http://arxiv.org/abs/2409.00851
Autor:
Fathalla, Efat Samir, Zargarzadeh, Sahar, Xin, Chunsheng, Wu, Hongyi, Jiang, Peng, Santos, Joao F., Kibilda, Jacek, da, Aloizio Pereira
This paper presents an experimental study on mmWave beam profiling on a mmWave testbed, and develops a machine learning model for beamforming based on the experiment data. The datasets we have obtained from the beam profiling and the machine learning
Externí odkaz:
http://arxiv.org/abs/2408.13403
Autor:
Bhalgat, Yash, Tschernezki, Vadim, Laina, Iro, Henriques, João F., Vedaldi, Andrea, Zisserman, Andrew
Egocentric videos present unique challenges for 3D scene understanding due to rapid camera motion, frequent object occlusions, and limited object visibility. This paper introduces a novel approach to instance segmentation and tracking in first-person
Externí odkaz:
http://arxiv.org/abs/2408.09860
Autor:
Ishida, Shu, Henriques, João F.
This work compares ways of extending Reinforcement Learning algorithms to Partially Observed Markov Decision Processes (POMDPs) with options. One view of options is as temporally extended action, which can be realized as a memory that allows the agen
Externí odkaz:
http://arxiv.org/abs/2407.18913
Autor:
Volpe, Giorgio, Araújo, Nuno A. M., Guix, Maria, Miodownik, Mark, Martin, Nicolas, Alvarez, Laura, Simmchen, Juliane, Di Leonardo, Roberto, Pellicciotta, Nicola, Martinet, Quentin, Palacci, Jérémie, Ng, Wai Kit, Saxena, Dhruv, Sapienza, Riccardo, Nadine, Sara, Mano, João F., Mahdavi, Reza, Adiels, Caroline Beck, Forth, Joe, Santangelo, Christian, Palagi, Stefano, Seok, Ji Min, Webster-Wood, Victoria A., Wang, Shuhong, Yao, Lining, Aghakhani, Amirreza, Barois, Thomas, Kellay, Hamid, Coulais, Corentin, van Hecke, Martin, Pierce, Christopher J., Wang, Tianyu, Chong, Baxi, Goldman, Daniel I., Reina, Andreagiovanni, Trianni, Vito, Volpe, Giovanni, Beckett, Richard, Nair, Sean P., Armstrong, Rachel
Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials, characterized by their activity, adaptability, and autonomy, emulate
Externí odkaz:
http://arxiv.org/abs/2407.10623
Autor:
Santos, Joao F., Huff, Alexandre, Campos, Daniel, Cardoso, Kleber V., Both, Cristiano B., DaSilva, Luiz A.
The Open Radio Access Network (O-RAN) Alliance proposes an open architecture that disaggregates the RAN and supports executing custom control logic in near-real time from third-party applications, the xApps. Despite O-RAN's efforts, the creation of x
Externí odkaz:
http://arxiv.org/abs/2407.09619
Autor:
Longa, Marian, Henriques, João F.
Unsupervised object detection using deep neural networks is typically a difficult problem with few to no guarantees about the learned representation. In this work we present the first unsupervised object detection method that is theoretically guarant
Externí odkaz:
http://arxiv.org/abs/2406.07284