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pro vyhledávání: '"Aasan, Marius"'
Vision Transformer (ViT) architectures traditionally employ a grid-based approach to tokenization independent of the semantic content of an image. We propose a modular superpixel tokenization strategy which decouples tokenization and feature extracti
Externí odkaz:
http://arxiv.org/abs/2408.07680
The intersection of vision and language is of major interest due to the increased focus on seamless integration between recognition and reasoning. Scene graphs (SGs) have emerged as a useful tool for multimodal image analysis, showing impressive perf
Externí odkaz:
http://arxiv.org/abs/2310.01842
Publikováno v:
de Oliveira Souza, Bruno Cesar Aasan, Marius Pedrini, Helio Ramírez Rivera, Adín . SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based Question Answering. 2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). 2023, 4642-4647. France: IEEE
Externí odkaz:
http://hdl.handle.net/10852/108242
Autor:
Aasan, Marius
Publikováno v:
Aasan, Marius. Invertible and Pseudo-Invertible Encoders: An Approach to Inverse Problems with Neural Networks. Master thesis, University of Oslo, 2021
Externí odkaz:
http://hdl.handle.net/10852/91228
https://www.duo.uio.no/bitstream/handle/10852/91228/8/Master___Marius_Final.pdf
https://www.duo.uio.no/bitstream/handle/10852/91228/8/Master___Marius_Final.pdf