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Found 4 papers, 2 papers with code
Cross-Scale Context Extracted Hashing for Fine-Grained Image Binary Encoding
Deep hashing has been widely applied to large-scale image retrieval tasks owing to efficient computation and low storage cost by encoding high-dimensional image data into binary codes.
2nd Place Solution to Google Landmark Retrieval 2020
Using this method, we got a public score of 0. 40176 and a private score of 0. 36278 and achieved 2nd place in the Google Landmark Retrieval Competition 2020.
DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features
Components orthogonal to the global image representation are then extracted from the local information.
Reconstructing Perceived Images from Brain Activity by Visually-guided Cognitive Representation and Adversarial Learning
In addition, we introduce a novel three-stage learning approach which enables the (cognitive) encoder to gradually distill useful knowledge from the paired (visual) encoder during the learning process.
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