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Found 4 papers, 2 papers with code
Two-stream joint matching method based on contrastive learning for few-shot action recognition
Although few-shot action recognition based on metric learning paradigm has achieved significant success, it fails to address the following issues: (1) inadequate action relation modeling and underutilization of multi-modal information; (2) challenges in handling video matching problems with different lengths and speeds, and video matching problems with misalignment of video sub-actions.
Forcing the Whole Video as Background: An Adversarial Learning Strategy for Weakly Temporal Action Localization
With video-level labels, weakly supervised temporal action localization (WTAL) applies a localization-by-classification paradigm to detect and classify the action in untrimmed videos.
Classification
Weakly-supervised Temporal Action Localization
+1
Parallelized Tensor Train Learning of Polynomial Classifiers
In pattern classification, polynomial classifiers are well-studied methods as they are capable of generating complex decision surfaces.
A Tensor Network Kalman filter with an application in recursive MIMO Volterra system identification
This article introduces a Tensor Network Kalman filter, which can estimate state vectors that are exponentially large without ever having to explicitly construct them.
Systems and Control
