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Found 6 papers, 4 papers with code
MuDreamer: Learning Predictive World Models without Reconstruction
In this paper, we present MuDreamer, a robust reinforcement learning agent that builds upon the DreamerV3 algorithm by learning a predictive world model without the need for reconstructing input signals.
Multilingual Audio-Visual Speech Recognition with Hybrid CTC/RNN-T Fast Conformer
Humans are adept at leveraging visual cues from lip movements for recognizing speech in adverse listening conditions.
Audio-Visual Efficient Conformer for Robust Speech Recognition
We improve previous lip reading methods using an Efficient Conformer back-end on top of a ResNet-18 visual front-end and by adding intermediate CTC losses between blocks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration
Using this method we can tackle the major issues in training transformer vision models, such as training instability, resolution gaps between pre-training and fine-tuning, and hunger on data.
Conformer and Blind Noisy Students for Improved Image Quality Assessment
Learning-based approaches for perceptual image quality assessment (IQA) usually require both the distorted and reference image for measuring the perceptual quality accurately.
Efficient conformer: Progressive downsampling and grouped attention for automatic speech recognition
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.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
