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RETRIEVAL.md

Papers

Lists 100+ papers on deep learning for image retrieval and hashing, each with links and brief metadata.

DavidZhangdw
May 2, 2026
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What this file does

Lists 100+ papers on deep learning for image retrieval and hashing, each with links and brief metadata.

When to use it

  • Starting a literature review on image retrieval
  • Looking for seminal papers on deep hashing methods
  • Finding code or project pages for a specific retrieval technique
  • Compiling a reading list for a course or survey

author: David Zhang category: deep_learning title: Image Retrieval date: 2019-12-21

Papers

Using Very Deep Autoencoders for Content-Based Image Retrieval

Learning High-level Image Representation for Image Retrieval via Multi-Task DNN using Clickthrough Data

Neural Codes for Image Retrieval

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Learning visual similarity for product design with convolutional neural networks

Exploiting Local Features from Deep Networks for Image Retrieval

Visual Search at Pinterest

Aggregating Deep Convolutional Features for Image Retrieval

Particular object retrieval with integral max-pooling of CNN activations

Group Invariant Deep Representations for Image Instance Retrieval

Where to Buy It: Matching Street Clothing Photos in Online Shops

Natural Language Object Retrieval

Deep Image Retrieval: Learning global representations for image search

End-to-end Learning of Deep Visual Representations for Image Retrieval

Bags of Local Convolutional Features for Scalable Instance Search

Faster R-CNN Features for Instance Search

Where to Focus: Query Adaptive Matching for Instance Retrieval Using Convolutional Feature Maps

Adversarial Training For Sketch Retrieval

Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks

Fast Training of Triplet-based Deep Binary Embedding Networks

Deep Relative Distance Learning: Tell the Difference Between Similar Vehicles

DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations

CNN Image Retrieval Learns from BoW: Unsupervised Fine-Tuning with Hard Examples

PicHunt: Social Media Image Retrieval for Improved Law Enforcement

SIFT Meets CNN: A Decade Survey of Instance Retrieval

The Sketchy Database: Learning to Retrieve Badly Drawn Bunnies

What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?

Image Retrieval with Deep Local Features and Attention-based Keypoints

Internet-Based Image Retrieval Using End-to-End Trained Deep Distributions

Compression of Deep Neural Networks for Image Instance Retrieval

Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval

Siamese Network of Deep Fisher-Vector Descriptors for Image Retrieval

Deep Geometric Retrieval

Context Aware Query Image Representation for Particular Object Retrieval

https://www.arxiv.org/abs/1703.01226

An End-to-End Approach to Natural Language Object Retrieval via Context-Aware Deep Reinforcement Learning

https://arxiv.org/abs/1703.07579

AMC: Attention guided Multi-modal Correlation Learning for Image Search

Video2Shop: Exactly Matching Clothes in Videos to Online Shopping Images

Deep image representations using caption generators

Visual Search at eBay

Sampling Matters in Deep Embedding Learning

One-Shot Fine-Grained Instance Retrieval

Selective Deep Convolutional Features for Image Retrieval

Class-Weighted Convolutional Features for Visual Instance Search

Learning a Repression Network for Precise Vehicle Search

https://arxiv.org/abs/1708.02386

SUBIC: A supervised, structured binary code for image search

Pruning Convolutional Neural Networks for Image Instance Retrieval

https://arxiv.org/abs/1707.05455

Image2song: Song Retrieval via Bridging Image Content and Lyric Words

Region-Based Image Retrieval Revisited

Beyond Part Models: Person Retrieval with Refined Part Pooling

https://arxiv.org/abs/1711.09349

Query-Adaptive R-CNN for Open-Vocabulary Object Detection and Retrieval

https://arxiv.org/abs/1711.09509

Saliency Weighted Convolutional Features for Instance Search

DeepStyle: Multimodal Search Engine for Fashion and Interior Design

https://arxiv.org/abs/1801.03002

From Selective Deep Convolutional Features to Compact Binary Representations for Image Retrieval

https://arxiv.org/abs/1802.02899

Web-Scale Responsive Visual Search at Bing

Approximate Query Matching for Image Retrieval

https://arxiv.org/abs/1803.05401

Object Captioning and Retrieval with Natural Language

https://arxiv.org/abs/1803.06152

Triplet-Center Loss for Multi-View 3D Object Retrieval

Collaborative Multi-modal deep learning for the personalized product retrieval in Facebook Marketplace

DeepFirearm: Learning Discriminative Feature Representation for Fine-grained Firearm Retrieval

Instance Search via Instance Level Segmentation and Feature Representation

https://arxiv.org/abs/1806.03576

Deep Feature Aggregation with Heat Diffusion for Image Retrieval

Single Shot Scene Text Retrieval

Learning Embeddings for Product Visual Search with Triplet Loss and Online Sampling

Attention-aware Generalized Mean Pooling for Image Retrieval

https://arxiv.org/abs/1811.00202

Hierarchy-based Image Embeddings for Semantic Image Retrieval

https://arxiv.org/abs/1811.09763

Instance-level Sketch-based Retrieval by Deep Triplet Classification Siamese Network

https://arxiv.org/abs/1811.11375

Detect-to-Retrieve: Efficient Regional Aggregation for Image Search

Learning with Average Precision: Training Image Retrieval with a Listwise Loss

A Benchmark on Tricks for Large-scale Image Retrieval

Hashing

Supervised Hashing for Image Retrieval via Image Representation Learning

Simultaneous Feature Learning and Hash Coding with Deep Neural Networks

Hashing by Deep Learning

Deep Semantic Ranking Based Hashing for Multi-Label Image Retrieval

Deep Learning of Binary Hash Codes for Fast Image Retrieval

Supervised Learning of Semantics-Preserving Hashing via Deep Neural Networks for Large-Scale Image Search

Bit-Scalable Deep Hashing with Regularized Similarity Learning for Image Retrieval and Person Re-identification

Deep Supervised Hashing for Fast Image Retrieval

Deep Hashing Network for Efficient Similarity Retrieval

Feature Learning based Deep Supervised Hashing with Pairwise Labels

Deep Cross-Modal Hashing

https://arxiv.org/abs/1602.02255

Cycle-Consistent Deep Generative Hashing for Cross-Modal Retrieval

https://arxiv.org/abs/1804.11013

SSDH: Semi-supervised Deep Hashing for Large Scale Image Retrieval

Deep Semantic-Preserving and Ranking-Based Hashing for Image Retrieval

Deep Hashing: A Joint Approach for Image Signature Learning

Transitive Hashing Network for Heterogeneous Multimedia Retrieval

Deep Residual Hashing

Deep Region Hashing for Efficient Large-scale Instance Search from Images

HashNet: Deep Learning to Hash by Continuation

Unsupervised Triplet Hashing for Fast Image Retrieval

Deep Sketch Hashing: Fast Free-hand Sketch-Based Image Retrieval

Learning Robust Hash Codes for Multiple Instance Image Retrieval

Simultaneous Feature Aggregating and Hashing for Large-scale Image Search

Learning to Hash

Hashing as Tie-Aware Learning to Rank

https://arxiv.org/abs/1705.08562

Deep Hashing Network for Unsupervised Domain Adaptation

Deep Binary Reconstruction for Cross-modal Hashing

A Revisit on Deep Hashings for Large-scale Content Based Image Retrieval

The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching

ForestHash: Semantic Hashing With Shallow Random Forests and Tiny Convolutional Networks

https://arxiv.org/abs/1711.08364

Supervised Hashing with End-to-End Binary Deep Neural Network

https://arxiv.org/abs/1711.08901

Transfer Adversarial Hashing for Hamming Space Retrieval

https://arxiv.org/abs/1712.04616

Dual Asymmetric Deep Hashing Learning

https://arxiv.org/abs/1801.08360

Attribute-Guided Network for Cross-Modal Zero-Shot Hashing

https://arxiv.org/abs/1802.01943

Deep Reinforcement Learning for Image Hashing

https://arxiv.org/abs/1802.02904

Hashing with Mutual Information

https://arxiv.org/abs/1803.00974

Zero-Shot Sketch-Image Hashing

Instance Similarity Deep Hashing for Multi-Label Image Retrieval

https://arxiv.org/abs/1803.02987

Deep Class-Wise Hashing: Semantics-Preserving Hashing via Class-wise Loss

Unsupervised Semantic Deep Hashing

https://arxiv.org/abs/1803.06911

SketchMate: Deep Hashing for Million-Scale Human Sketch Retrieval

Improving Deep Binary Embedding Networks by Order-aware Reweighting of Triplets

Deep Semantic Hashing with Generative Adversarial Networks

Deep Ordinal Hashing with Spatial Attention

https://arxiv.org/abs/1805.02459

Efficient end-to-end learning for quantizable representations

Unsupervised Deep Image Hashing through Tag Embeddings

https://arxiv.org/abs/1806.05804

Adversarial Learning for Fine-grained Image Search

https://arxiv.org/abs/1807.02247

Error Correction Maximization for Deep Image Hashing

https://arxiv.org/abs/1808.01942

Deep Priority Hashing

Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing

https://arxiv.org/abs/1809.02302

Deep LDA Hashing

https://arxiv.org/abs/1810.03402

Deep Triplet Quantization

SADIH: Semantic-Aware DIscrete Hashing

Feature Pyramid Hashing

https://arxiv.org/abs/1904.02325

Global Hashing System for Fast Image Search

https://arxiv.org/abs/1904.08685

Cross Modal Retrieval

Cross-domain Image Retrieval with a Dual Attribute-aware Ranking Network

Deep Learning for Content-Based, Cross-Modal Retrieval of Videos and Music

Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval

MHTN: Modal-adversarial Hybrid Transfer Network for Cross-modal Retrieval

https://arxiv.org/abs/1708.04308

Cross-Domain Image Retrieval with Attention Modeling

https://arxiv.org/abs/1709.01784

Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models

https://arxiv.org/abs/1711.06420

HashGAN:Attention-aware Deep Adversarial Hashing for Cross Modal Retrieval

https://arxiv.org/abs/1711.09347

Objects that Sound

Cross-modal Embeddings for Video and Audio Retrieval

Learnable PINs: Cross-Modal Embeddings for Person Identity

Revisiting Cross Modal Retrieval

Projects

HABIR哈希图像检索工具箱

Video Indexing / Retrieval

Face Video Retrieval via Deep Learning of Binary Hash Representations

Deep Learning Based Semantic Video Indexing and Retrieval

Learning Joint Representations of Videos and Sentences with Web Image Search

Multi-View Product Image Search Using ConvNets Features

Generalisation and Sharing in Triplet Convnets for Sketch based Visual Search

Binary Subspace Coding for Query-by-Image Video Retrieval

Action Search: Learning to Search for Human Activities in Untrimmed Videos

https://arxiv.org/abs/1706.04269

Deep Supervised Hashing with Triplet Labels

Supervised Deep Hashing for Hierarchical Labeled Data

Localizing Moments in Video with Natural Language

Dress like a Star: Retrieving Fashion Products from Videos

Deep Hashing with Category Mask for Fast Video Retrieval

https://arxiv.org/abs/1712.08315

Focus: Querying Large Video Datasets with Low Latency and Low Cost

https://arxiv.org/abs/1801.03493

Text-to-Clip Video Retrieval with Early Fusion and Re-Captioning

Learning to Rank

Simple to Complex Cross-modal Learning to Rank

Deep Metric Learning

Deep metric learning using Triplet network

Improved Deep Metric Learning with Multi-class N-pair Loss Objective

Metric Learning with Adaptive Density Discrimination

Hard-Aware Deeply Cascaded Embedding

Learnable Structured Clustering Framework for Deep Metric Learning

Deep Metric Learning via Lifted Structured Feature Embedding

Cross-modal Deep Metric Learning with Multi-task Regularization

Smart Mining for Deep Metric Learning

https://arxiv.org/abs/1704.01285

DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer

Deep Metric Learning with Angular Loss

Deep Metric Learning with BIER: Boosting Independent Embeddings Robustly

https://arxiv.org/abs/1801.04815

Directional Statistics-based Deep Metric Learning for Image Classification and Retrieval

https://arxiv.org/abs/1802.09662

Generalization in Metric Learning: Should the Embedding Layer be the Embedding Layer?

Deep Metric Learning

Attention-based Ensemble for Deep Metric Learning

https://arxiv.org/abs/1804.00382

Online Deep Metric Learning

https://arxiv.org/abs/1805.05510

Deep Randomized Ensembles for Metric Learning

Deep Metric Learning with Hierarchical Triplet Loss

Ranked List Loss for Deep Metric Learning

Hardness-Aware Deep Metric Learning

Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning

Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning

Deep Metric Learning Beyond Binary Supervision

SoftTriple Loss: Deep Metric Learning Without Triplet Sampling

The Group Loss for Deep Metric Learning

https://arxiv.org/abs/1912.00385

Talks / Slides

TiefVision: end-to-end image similarity search engine

Projects

图像检索：CNN卷积神经网络与实战

CNN for Image Retrieval

Visual Search Server

Vehicle Retrieval: vehicle image retrieval using k CNNs ensemble method

A visual search engine based on Elasticsearch and Tensorflow

Siamese and triplet networks with online pair/triplet mining in PyTorch

https://github.com/adambielski/siamese-triplet

Triplet Loss and Online Triplet Mining in TensorFlow

Blogs

Where can I buy a chair like that? – This app will tell you

Using Sketches to Search for Products Online

Tutorials

Deep Image Retrieval: Learning global representations for image search

Image Instance Retrieval: Overview of state-of-the-art

What's inside

Two sections: Image Retrieval (80+ entries) and Hashing (20+ entries), each with title, venue, and links.

Change this for your project

  • Replace David Zhang in the YAML front matter with your own name
  • Replace deep_learning in the category field if your focus differs
  • Replace 2019-12-21 in the date field with the current date

Where it goes

Keep it in your repository where the agent or team that needs it will read it.

Worth borrowing

  • Organizing papers by sub-topic (retrieval vs. hashing) for easy scanning
  • Including project pages and code links alongside each paper entry

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