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Found 4 papers, 3 papers with code
Training-free Zero-shot Composed Image Retrieval via Weighted Modality Fusion and Similarity
Our approach is simple, easy to implement, and its effectiveness is validated through experiments on the FashionIQ and CIRR datasets.
Class-incremental Continual Learning for Instance Segmentation with Image-level Weak Supervision
To our knowledge, this is the first work on weakly-supervised continual learning for instance segmentation of images.
Latent Feature Representation via Unsupervised Learning for Pattern Discovery in Massive Electron Microscopy Image Volumes
We propose a method to facilitate exploration and analysis of new large data sets.
Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks
SSDH is simple and can be realized by a slight enhancement of an existing deep architecture for classification; yet it is effective and outperforms other hashing approaches on several benchmarks and large datasets.
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