Papers Zero-shot Image Retrieval
“Zero-shot Image Retrieval” 태그가 달린 논문 29편 · 필터 해제
Full-attention based Neural Architecture Search using Context Auto-regression
Self-attention architectures have emerged as a recent advancement for improving the performance of vision tasks. Manual determination of the architecture for self-attention networks relies on the experience of experts an…
Fine-Grained Image Recognitionimage-classificationImage ClassificationImage Retrieval+4Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval
Visual-semantic embedding is an interesting research topic because it is useful for various tasks, such as visual question answering (VQA), image-text retrieval, image captioning, and scene graph generation. In this pape…
Graph GenerationImage CaptioningImage RetrievalImage-text Retrieval+10Attribute-Modulated Generative Meta Learning for Zero-Shot Classification
Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to semantically related unseen classes, which are absent during training. The promising strategies for ZSL are to synthesize visual features of unseen…
AttributeClassificationGeneral ClassificationImage Retrieval+5Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers
Recently multimodal transformer models have gained popularity because their performance on language and vision tasks suggest they learn rich visual-linguistic representations. Focusing on zero-shot image retrieval tasks,…
Image RetrievalRetrievalSelf-Supervised LearningZero-shot Image RetrievalHybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval
In zero-shot image retrieval (ZSIR) task, embedding learning becomes more attractive, however, many methods follow the traditional metric learning idea and omit the problems behind zero-shot settings. In this paper, we f…
Image RetrievalMetric LearningRetrievalZero-shot Image RetrievalLearning with Succinct Common Representation Based on Wyner's Common Information
A new bimodal generative model is proposed for generating conditional and joint samples, accompanied with a training method with learning a succinct bottleneck representation. The proposed model, dubbed as the variationa…
Density Ratio EstimationImage RetrievalRepresentation LearningRetrieval+1Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering
Deep metric learning has been widely applied in many computer vision tasks, and recently, it is more attractive in \emph{zero-shot image retrieval and clustering}(ZSRC) where a good embedding is requested such that the u…
ClusteringImage RetrievalMetric LearningRetrieval+1Attribute-Guided Network for Cross-Modal Zero-Shot Hashing
Zero-Shot Hashing aims at learning a hashing model that is trained only by instances from seen categories but can generate well to those of unseen categories. Typically, it is achieved by utilizing a semantic embedding s…
AttributeCross-Modal RetrievalImage RetrievalRetrieval+1Zero-Shot Hashing via Transferring Supervised Knowledge
Hashing has shown its efficiency and effectiveness in facilitating large-scale multimedia applications. Supervised knowledge e.g. semantic labels or pair-wise relationship) associated to data is capable of significantly …
Image RetrievalRetrievalZero-shot Image Retrieval