In this paper, we propose an end-to-end local similarity learning framework to tackle these problems. By applying a correlation layer to the locally aggregated ...
ABSTRACT. Many state-of-the-art object retrieval algorithms aggregate acti- vations of convolutional neural networks into a holistic compact.
Oct 21, 2019 · ABSTRACT. Many state-of-the-art object retrieval algorithms aggregate acti- vations of convolutional neural networks into a holistic compact.
May 5, 2023 · SUMMARY. Convolutional Neural Networks (CNNs) have recently demonstrated outstanding performance in image retrieval tasks. Local con-.
Convolutional Neural Networks (CNNs) have recently demonstrated outstanding performance in image retrieval tasks. Local convolutional features extracted by ...
Specifically, we first define three forms of local similarity tensors (LSTs), which take into account information about local regions as well as spatial ...
Jul 20, 2019 · Conference Paper: Learning Local Similarity with Spatial Relations for Object Retrieval ; Chen, ZKuang, ZZhang, WWong, KKY · 2019 · ACM Multimedia.
Apr 17, 2024 · During the retrieval process, our method replicates the spatial encoding procedure to retrieve images with similar spatial structures.
In this context, taking into account the spatial organization of objects is fundamental to increase both the understanding and the accuracy of the perceived ...
Oct 8, 2020 · We show that while general spatial information does transfer between real and virtual environments, there are several limitations of the virtual experience.