11 citations · 20 across the 8 of their papers we have counts for
8 papers
Accurate and Efficient World Modeling with Masked Latent Transformers
Maxime Burchi, Radu Timofte
The Dreamer algorithm has recently obtained remarkable performance across diverse environment domains by training powerful agents with simulated trajectories. However, the compress…
Learning Transformer-based World Models with Contrastive Predictive Coding
Maxime Burchi, Radu Timofte
The DreamerV3 algorithm recently obtained remarkable performance across diverse environment domains by learning an accurate world model based on Recurrent Neural Networks (RNNs). F…
MuDreamer: Learning Predictive World Models without Reconstruction
Maxime Burchi, Radu Timofte
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…
Multilingual Audio-Visual Speech Recognition with Hybrid CTC/RNN-T Fast Conformer
Maxime Burchi, Krishna C. Puvvada, Jagadeesh Balam +2
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 a…
Audio-Visual Efficient Conformer for Robust Speech Recognition
Maxime Burchi, Radu Timofte
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 a…
Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration
Marcos V. Conde, Ui-Jin Choi, Maxime Burchi +1
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 video…
Conformer and Blind Noisy Students for Improved Image Quality Assessment
Marcos V. Conde, Maxime Burchi, Radu Timofte
Generative models for image restoration, enhancement, and generation have significantly improved the quality of the generated images. Surprisingly, these models produce more pleasa…
Efficient conformer: Progressive downsampling and grouped attention for automatic speech recognition
Maxime Burchi, Valentin Vielzeuf
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…