Self-supervised Video Retrieval
9 papers with code • 2 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Self-supervised Video Retrieval
| Trend | Dataset | Best Model | Paper | Code | Compare |
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UCF101
HMDB51
Most implemented papers
Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework
BestJuly/Inter-intra-video-contrastive-learning
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With the proposed Inter-Intra Contrastive (IIC) framework, we can train spatio-temporal convolutional networks to learn video representations.
Similarity Contrastive Estimation for Image and Video Soft Contrastive Self-Supervised Learning
A good data representation should contain relations between the instances, or semantic similarity and dissimilarity, that contrastive learning harms by considering all negatives as noise.
Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning
BestJuly/VCP
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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.
Video Playback Rate Perception for Self-Supervised Spatio-Temporal Representation Learning
The generative perception model acts as a feature decoder to focus on comprehending high temporal resolution and short-term representation by introducing a motion-attention mechanism.
Pretext-Contrastive Learning: Toward Good Practices in Self-supervised Video Representation Leaning
BestJuly/Pretext-Contrastive-Learning
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It is convenient to treat PCL as a standard training strategy and apply it to many other works in self-supervised video feature learning.
TCLR: Temporal Contrastive Learning for Video Representation
DAVEISHAN/TCLR
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However, prior work on contrastive learning for video data has not explored the effect of explicitly encouraging the features to be distinct across the temporal dimension.
Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting
Instance-level contrastive learning techniques, which rely on data augmentation and a contrastive loss function, have found great success in the domain of visual representation learning.
Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Synchronicity
We present CrissCross, a self-supervised framework for learning audio-visual representations.
SLIC: Self-Supervised Learning with Iterative Clustering for Human Action Videos
rvl-lab-utoronto/video_similarity_search
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CVPR 2022
One of the key reasons for this is that sampling pairs of similar video clips, a required step for many self-supervised contrastive learning methods, is currently done conservatively to avoid false positives.
