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Graph Regularized Encoder-Decoder Networks for Image Representation Learning

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Microsoft COCO: Common Objects in Context
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The Approximation of One Matrix by Another of Lower Rank
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Weakly-supervised Semantic Guided Hashing for Social Image Retrieval
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Learning a Similarity Metric Discriminatively, with Application to Face Verification
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Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
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Show and tell: A neural image caption generator
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Joint Unsupervised Learning of Deep Representations and Image Clusters
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Knowing When to Look: Adaptive Attention via a Visual Sentinel for Image Captioning
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A Graph Regularized Deep Neural Network for Unsupervised Image Representation Learning
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00878openalex-snapshot
State-Relabeling Adversarial Active Learning
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Adaptive Reconstruction Network for Weakly Supervised Referring Expression Grounding
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Generating Diverse and Descriptive Image Captions Using Visual Paraphrases
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Deep Comprehensive Correlation Mining for Image Clustering
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Manifold Regularized Discriminative Nonnegative Matrix Factorization With Fast Gradient Descent
inferredcites →https://doi.org/10.1109/tip.2019.2908774openalex-snapshot
Online Asymmetric Metric Learning With Multi-Layer Similarity Aggregation for Cross-Modal Retrieval
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Document clustering using locality preserving indexing
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Learning Hierarchical Semantic Description Via Mixed-Norm Regularization for Image Understanding
inferredcites →https://doi.org/10.1109/tmm.2015.2477035openalex-snapshot
Weakly Supervised Deep Metric Learning for Community-Contributed Image Retrieval
inferredcites →https://doi.org/10.1109/tmm.2018.2823900openalex-snapshot
Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification
inferredcites →https://doi.org/10.1109/tmm.2018.2875512openalex-snapshot
Learning Multi-View Representation With LSTM for 3-D Shape Recognition and Retrieval
inferredcites →https://doi.org/10.1109/tmm.2019.2912735openalex-snapshot
SkeletonNet: A Hybrid Network With a Skeleton-Embedding Process for Multi-View Image Representation Learning
inferredcites →https://doi.org/10.1109/tnnls.2017.2691725openalex-snapshot
Robust Structured Nonnegative Matrix Factorization for Image Representation
inferredcites →https://doi.org/10.1109/tpami.2010.231openalex-snapshot
Graph Regularized Nonnegative Matrix Factorization for Data Representation
inferredcites →https://doi.org/10.1109/tpami.2015.2400461openalex-snapshot
Robust Structured Subspace Learning for Data Representation
inferredcites →https://doi.org/10.1109/tpami.2016.2598339openalex-snapshot
Deep Visual-Semantic Alignments for Generating Image Descriptions
inferredcites →https://doi.org/10.1109/tpami.2018.2852750openalex-snapshot
Deep Collaborative Embedding for Social Image Understanding
inferredcites →https://doi.org/10.1126/science.1127647openalex-snapshot
Reducing the Dimensionality of Data with Neural Networks
inferredcites →https://doi.org/10.1126/science.290.5500.2323openalex-snapshot
Nonlinear Dimensionality Reduction by Locally Linear Embedding
inferredcites →https://doi.org/10.1145/1390156.1390294openalex-snapshot
Extracting and composing robust features with denoising autoencoders
inferredcites →https://doi.org/10.1145/3240508.3240535openalex-snapshot
Joint Global and Co-Attentive Representation Learning for Image-Sentence Retrieval
inferredcites →https://doi.org/10.1145/3328994openalex-snapshot
Learning Click-Based Deep Structure-Preserving Embeddings with Visual Attention
inferredcites →https://doi.org/10.1145/3343031.3350940openalex-snapshot
Learning Fragment Self-Attention Embeddings for Image-Text Matching
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A Hierarchical CNN-RNN Approach for Visual Emotion Classification
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Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
inferredcites →https://doi.org/10.1609/aaai.v26i1.8289openalex-snapshot
Unsupervised Feature Selection Using Nonnegative Spectral Analysis
inferredcites →https://doi.org/10.1609/aaai.v28i1.8916openalex-snapshot
Learning Deep Representations for Graph Clustering
inferredcites →https://doi.org/10.1609/aaai.v29i1.9598openalex-snapshot
Large-Scale Multi-View Spectral Clustering via Bipartite Graph
inferredcites →https://doi.org/10.3115/v1/d14-1179openalex-snapshot
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
inferredcites →https://doi.org/10.3115/v1/p14-1068openalex-snapshot
Learning Grounded Meaning Representations with Autoencoders
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Neural Machine Translation by Jointly Learning to Align and Translate
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Explaining and Harnessing Adversarial Examples
inferredcites →https://doi.org/10.48550/arxiv.1511.05045openalex-snapshot
Handcrafted Local Features are Convolutional Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1605.05396openalex-snapshot
Generative Adversarial Text to Image Synthesis
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Greedy Layer-Wise Training of Deep Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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inferred← citeshttps://doi.org/10.1109/tmm.2022.3141947openalex-snapshot
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Low-Rank Correlation Learning for Unsupervised Domain Adaptation
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3214993openalex-snapshot
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inferred← citeshttps://doi.org/10.12785/ijcds/150132openalex-snapshot
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inferred← citeshttps://doi.org/10.37648/ijiest.v12i01.007openalex-snapshot
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