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Found 6 papers, 3 papers with code
DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue Dataset
Through this pipeline, we introduce DialogCC, a high-quality and diverse multi-modal dialogue dataset that surpasses existing datasets in terms of quality and diversity in human evaluation.
Group Generalized Mean Pooling for Vision Transformer
As ViT groups the channels via a multi-head attention mechanism, grouping the channels by GGeM leads to lower head-wise dependence while amplifying important channels on the activation maps.
Back from the future: bidirectional CTC decoding using future information in speech recognition
In this paper, we propose a simple but effective method to decode the output of Connectionist Temporal Classifier (CTC) model using a bi-directional neural language model.
Learning with Memory-based Virtual Classes for Deep Metric Learning
This can be undesirable for DML, where training and test data exhibit entirely different classes.
Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning
One of the main purposes of deep metric learning is to construct an embedding space that has well-generalized embeddings on both seen (training) classes and unseen (test) classes.
Audio Source Separation Using a Deep Autoencoder
This paper proposes a novel framework for unsupervised audio source separation using a deep autoencoder.
