DeepAI AI Chat
Log In Sign Up

Needle In A Haystack, Fast: Benchmarking Image Perceptual Similarity Metrics At Scale

by   Cyril Vallez, et al.

The advent of the internet, followed shortly by the social media made it ubiquitous in consuming and sharing information between anyone with access to it. The evolution in the consumption of media driven by this change, led to the emergence of images as means to express oneself, convey information and convince others efficiently. With computer vision algorithms progressing radically over the last decade, it is become easier and easier to study at scale the role of images in the flow of information online. While the research questions and overall pipelines differ radically, almost all start with a crucial first step - evaluation of global perceptual similarity between different images. That initial step is crucial for overall pipeline performance and processes most images. A number of algorithms are available and currently used to perform it, but so far no comprehensive review was available to guide the choice of researchers as to the choice of an algorithm best suited to their question, assumptions and computational resources. With this paper we aim to fill this gap, showing that classical computer vision methods are not necessarily the best approach, whereas a pair of relatively little used methods - Dhash perceptual hash and SimCLR v2 ResNets achieve excellent performance, scale well and are computationally efficient.


page 12

page 13

page 14

page 17

page 20


R-LPIPS: An Adversarially Robust Perceptual Similarity Metric

Similarity metrics have played a significant role in computer vision to ...

Deep Learning and Computer Vision Techniques for Microcirculation Analysis: A Review

The analysis of microcirculation images has the potential to reveal earl...

Perceptual Attacks of No-Reference Image Quality Models with Human-in-the-Loop

No-reference image quality assessment (NR-IQA) aims to quantify how huma...

Identifying and Mitigating Flaws of Deep Perceptual Similarity Metrics

Measuring the similarity of images is a fundamental problem to computer ...

Hierarchical Auto-Regressive Model for Image Compression Incorporating Object Saliency and a Deep Perceptual Loss

We propose a new end-to-end trainable model for lossy image compression ...