Multi-negative samples with Generative Adversarial Networks ...
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Jun 21, 2020 · In this paper, we propose to utilize generated virtual images and multiple negative samples to simultaneously learn image representations for the task of image ...
Jun 21, 2020 · In this paper, we propose to utilize generated virtual images and multiple negative samples to simultaneously learn image representations for the task of image ...
To understand the development of frontal face generation models and grasp the current research hotspots and trends, existing methods based on 3D models, ...
In our method, we first utilize the Generative Adversarial Networks in a semi-supervised fashion to produce virtual images with an adversarial loss. Second, ...
This paper proposes a novel multiple negative samples model based on GAN (MNS-GAN) to increase intra-modal discrimination.
Comprehensive experiments show that our proposed MNS-GAN method outperforms the state-of- the-art cross-modal retrieval methods. Keywords—Cross-modal retrieval, ...
Apr 23, 2023 · Abstract—Negative sampling (NS) is widely used in knowledge graph embedding (KGE), which aims to generate negative triples.
Missing: retrieval. | Show results with:retrieval.
Multi-negative Samples with Generative Adversarial Networks for Image Retrieval. Article. Jun 2019; NEUROCOMPUTING. Ruifan Li · Xuesen Zhang · Guang Chen ...
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This repository collects 100 papers related to negative sampling methods, covering multiple research fields such as Recommendation Systems (RS), Computer ...
Sep 8, 2020 · This section provides a brief review of the most recent state-of-the-art approaches carried out on the topics of learning from imbalanced data, ...