Self-Supervised Contrastive Learning model for video dataset?

This page summarizes the projects mentioned and recommended in the original post on /r/learnmachinelearning
simclr contrastive-learning representation-learning self-supervised-learning unsupervised-learning

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured

  • simclr

    SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

    • My data consists of binary labels (normal & anomalous) where the videos are already broken up into frames in the directory, I'm looking for a model where I can feed a normal-labeled video alongside an anomalous-labeled video like visualized in this example from the SimCLR Repo, a dog will represent the normal video and the chair the anomalous video.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

    InfluxDB logo
NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts

  • Positive and Negative Sampling Strategies for Representation Learning in Semantic Search

    2 projects | /r/LanguageTechnology | 25 Mar 2023

  • [D] Why is random cropping necessary in SimCLR?

    1 project | /r/MachineLearning | 30 Sep 2022

  • [R] Deep Learning with a Small Training Batch (or Lack Thereof). Part 1

    5 projects | /r/MachineLearning | 29 Aug 2022

  • [D] Current trends in computer vision related to unsupervised learning

    2 projects | /r/MachineLearning | 6 Aug 2022

  • [P] Choosing a self-supervised learning framework that's easy to use

    4 projects | /r/MachineLearning | 18 Jan 2022