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Found 5 papers, 1 papers with code
Multimodal High-order Relation Transformer for Scene Boundary Detection
Scene boundary detection breaks down long videos into meaningful story-telling units and plays a crucial role in high-level video understanding.
Vision Pair Learning: An Efficient Training Framework for Image Classification
Transformer is a potentially powerful architecture for vision tasks.
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective
Under this brand-new scenario, we propose Distortion Relation guided Transfer Learning (DRTL) for the few-shot RealSR by transferring the rich restoration knowledge from auxiliary distortions (i. e., synthetic distortions) to the target RealSR under the guidance of distortion relation.
TA2N: Two-Stage Action Alignment Network for Few-shot Action Recognition
The first stage locates the action by learning a temporal affine transform, which warps each video feature to its action duration while dismissing the action-irrelevant feature (e. g. background).
Uncertainty Guided Collaborative Training for Weakly Supervised Temporal Action Detection
To alleviate this problem, we propose a novel Uncertainty Guided Collaborative Training (UGCT) strategy, which mainly includes two key designs: (1) The first design is an online pseudo label generation module, in which the RGB and FLOW streams work collaboratively to learn from each other.
