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Cross-modal correlation learning for clustering on image ...
https://dl.acm.org/doi/10.1145/1291233.1291290#:~:text=It%20is%20interesting%20and%20challenging%20to%20explore%20correlations,help%20identify%20images%20%28or%20audios%29%20of%20certain%20semantics.
Cross-modal correlation learning for clustering on image ...
https://dl.acm.org/doi/10.1145/1291233.1291290
It is interesting and challenging to explore correlations between different datasets and utilize such correlations for the clustering on these datasets. Cross-modal correlation between images and audios can help identify images (or audios) of certain semantics. However, the heterogeneous problem makes it difficult to learn cross-modal correlation between visual …
Cross-modal correlation learning for clustering on image ...
https://www.researchgate.net/publication/221572243_Cross-modal_correlation_learning_for_clustering_on_image-audio_dataset
[24] learned cross-modal correlation between visual and auditory feature spaces, and treated such correlation as complementary information for …
Self-Supervised Learning by Cross-Modal Audio-Video …
https://proceedings.neurips.cc/paper/2020/file/6f2268bd1d3d3ebaabb04d6b5d099425-Paper.pdf
on this intuition, we propose Cross-Modal Deep Clustering (XDC), a novel self-supervised method that leverages unsupervised clustering in one modality (e.g., audio) as a supervisory signal for the other modality (e.g., video). This cross-modal supervision helps XDC utilize the semantic correlation and the differences between the two modalities.
Self-Supervised Learning by Cross-Modal Audio-Video …
https://deepai.org/publication/self-supervised-learning-by-cross-modal-audio-video-clustering
Cross-Modal Deep Clustering (XDC). Each encoder in this model relies exclusively on the clusters learned from the other modality as the supervisory signal. At each deep clustering iteration, XDC clusters the audio deep features, F a, and uses their cluster assignments as pseudo-labels to train the visual encoder, Ev.
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
https://paperswithcode.com/paper/self-supervised-learning-by-cross-modal-audio
A cross-media distance metric learning framework based on ...
https://dlnext.acm.org/doi/10.1007/s11280-015-0342-4
With the explosion of multimedia data, it is usual that different multimedia data often coexist in web repositories. Accordingly, it is more and more important to explore underlying intricate cross-media correlation instead of single-modality distance ...
Cross-modal Embeddings for Video and Audio Retrieval | …
https://deepai.org/publication/cross-modal-embeddings-for-video-and-audio-retrieval
A recent study also explored the cross-modal relations between the two modalities but using images with people talking and speech. It is done through Canonical Correlation Analysis (CCA) and cross-modal factor analysis. Also applying CCA, uses visual and sound features and common subspace features for aiding clustering in image-audio datasets.
GitHub - IMKBLE/CMSC-DCCA
https://github.com/IMKBLE/CMSC-DCCA
Introduction: For cross-modal subspace clustering, the key point is how to exploit the correlation information between cross-modal data. However, most hierarchical and structural correlation information among cross-modal data cannot be well exploited due to its high-dimensional non-linear property.
Understanding visual-auditory correlation from ...
https://link.springer.com/article/10.1631/jzus.A071191
Cross-media retrieval is an interesting research topic, which seeks to remove the barriers among different modalities. To enable cross-media retrieval, it is needed to find the correlation measures between heterogeneous low-level features and to judge the semantic similarity. This paper presents a novel approach to learn cross-media correlation between visual features and …
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