Image Similarity Search
13 papers with code • 0 benchmarks • 1 datasets
Image credit: The 2021 Image Similarity Dataset and Challenge
Benchmarks
These leaderboards are used to track progress in Image Similarity Search
Libraries
Use these libraries to find Image Similarity Search models and implementations
DISC21
Latest papers
Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain
SteveImmanuel/OEM-Few-Shot-Learnable-Prompt
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Few-shot segmentation is a task to segment objects or regions of novel classes within an image given only a few annotated examples.
Deep Hashing via Householder Quantization
Hashing is at the heart of large-scale image similarity search, and recent methods have been substantially improved through deep learning techniques.
CorrEmbed: Evaluating Pre-trained Model Image Similarity Efficacy with a Novel Metric
In this paper, we evaluate the viability of the image embeddings from numerous pre-trained computer vision models using a novel approach named CorrEmbed.
Weakly-Supervised Conditional Embedding for Referred Visual Search
simon-lepage/condvit-lrvsf
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This paper introduces a new challenge for image similarity search in the context of fashion, addressing the inherent ambiguity in this domain stemming from complex images.
ElasticHash: Semantic Image Similarity Search by Deep Hashing with Elasticsearch
It is based on a deep hashing model to learn hash codes for fine-grained image similarity search in natural images and a two-stage method for efficiently searching binary hash codes using Elasticsearch (ES).
Global Proxy-based Hard Mining for Visual Place Recognition
These proxy representations are thus used to construct a global index that encompasses the similarities between all places in the dataset, allowing for highly informative mini-batch sampling at each training iteration.
Intra-class Adaptive Augmentation with Neighbor Correction for Deep Metric Learning
They have overlooked the wide characteristic changes of different classes and can not model abundant intra-class variations for generations.
Learning an Adaptation Function to Assess Image Visual Similarities
VieVie31/visual-similarity
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As a consequence, such features are powerful to compare semantically related images but not really efficient to compare images visually similar but semantically unrelated.
Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News
nguyenvo09/EMNLP2020
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EMNLP 2020
The search can directly warn fake news posters and online users (e. g. the posters' followers) about misinformation, discourage them from spreading fake news, and scale up verified content on social media.
E-LPIPS: Robust Perceptual Image Similarity via Random Transformation Ensembles
mkettune/elpips
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It has been recently shown that the hidden variables of convolutional neural networks make for an efficient perceptual similarity metric that accurately predicts human judgment on relative image similarity assessment.
