Search Results for author:
Found 5 papers, 3 papers with code
Tubelet-Contrastive Self-Supervision for Video-Efficient Generalization
By simulating different tubelet motions and applying transformations, such as scaling and rotation, we introduce motion patterns beyond what is present in the pretraining data.
How Severe is Benchmark-Sensitivity in Video Self-Supervised Learning?
Despite the recent success of video self-supervised learning models, there is much still to be understood about their generalization capability.
Skeleton-Contrastive 3D Action Representation Learning
In particular, we propose inter-skeleton contrastive learning, which learns from multiple different input skeleton representations in a cross-contrastive manner.
Feature-Supervised Action Modality Transfer
This paper strives for action recognition and detection in video modalities like RGB, depth maps or 3D-skeleton sequences when only limited modality-specific labeled examples are available.
Cross-modal knowledge distillation for action recognition
To this end, we extract the knowledge of the trained teacher network for the source modality and transfer it to a small ensemble of student networks for the target modality.
