Self-Supervised Action Recognition

27 papers with code • 6 benchmarks • 4 datasets

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Most implemented papers

Contrastive Multiview Coding

HobbitLong/CMC ECCV 2020

We analyze key properties of the approach that make it work, finding that the contrastive loss outperforms a popular alternative based on cross-view prediction, and that the more views we learn from, the better the resulting representation captures underlying scene semantics.

Spatiotemporal Contrastive Video Representation Learning

tensorflow/models CVPR 2021

Our representations are learned using a contrastive loss, where two augmented clips from the same short video are pulled together in the embedding space, while clips from different videos are pushed away.

Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework

BestJuly/Inter-intra-video-contrastive-learning 6 Aug 2020

With the proposed Inter-Intra Contrastive (IIC) framework, we can train spatio-temporal convolutional networks to learn video representations.

A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning

facebookresearch/SlowFast CVPR 2021

We present a large-scale study on unsupervised spatiotemporal representation learning from videos.

Unsupervised Representation Learning by Sorting Sequences

HsinYingLee/OPN ICCV 2017

We present an unsupervised representation learning approach using videos without semantic labels.

007: Democratically Finding The Cause of Packet Drops

behnazak/Vigil-007SourceCode 20 Feb 2018

Network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur.

Video Representation Learning by Dense Predictive Coding

TengdaHan/DPC 10 Sep 2019

The objective of this paper is self-supervised learning of spatio-temporal embeddings from video, suitable for human action recognition.

Self-Supervised Learning by Cross-Modal Audio-Video Clustering

HumamAlwassel/XDC NeurIPS 2020

To the best of our knowledge, XDC is the first self-supervised learning method that outperforms large-scale fully-supervised pretraining for action recognition on the same architecture.

Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning

BestJuly/VCP 2 Jan 2020

As a proxy task, it converts rich self-supervised representations into video clip operations (options), which enhances the flexibility and reduces the complexity of representation learning.