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pro vyhledávání: '"Burchi, Maxime"'
Autor:
Burchi, Maxime, Timofte, Radu
The DreamerV3 agent recently demonstrated state-of-the-art performance in diverse domains, learning powerful world models in latent space using a pixel reconstruction loss. However, while the reconstruction loss is essential to Dreamer's performance,
Externí odkaz:
http://arxiv.org/abs/2405.15083
Humans are adept at leveraging visual cues from lip movements for recognizing speech in adverse listening conditions. Audio-Visual Speech Recognition (AVSR) models follow similar approach to achieve robust speech recognition in noisy conditions. In t
Externí odkaz:
http://arxiv.org/abs/2405.12983
Autor:
Burchi, Maxime, Timofte, Radu
End-to-end Automatic Speech Recognition (ASR) systems based on neural networks have seen large improvements in recent years. The availability of large scale hand-labeled datasets and sufficient computing resources made it possible to train powerful d
Externí odkaz:
http://arxiv.org/abs/2301.01456
Compression plays an important role on the efficient transmission and storage of images and videos through band-limited systems such as streaming services, virtual reality or videogames. However, compression unavoidably leads to artifacts and the los
Externí odkaz:
http://arxiv.org/abs/2209.11345
Generative models for image restoration, enhancement, and generation have significantly improved the quality of the generated images. Surprisingly, these models produce more pleasant images to the human eye than other methods, yet, they may get a low
Externí odkaz:
http://arxiv.org/abs/2204.12819
Efficient conformer: Progressive downsampling and grouped attention for automatic speech recognition
Autor:
Burchi, Maxime, Vielzeuf, Valentin
Publikováno v:
ASRU 2021, Dec 2021, Cartagena, Colombia
The recently proposed Conformer architecture has shown state-of-the-art performances in Automatic Speech Recognition by combining convolution with attention to model both local and global dependencies. In this paper, we study how to reduce the Confor
Externí odkaz:
http://arxiv.org/abs/2109.01163