4 papers
Hierarchical Relation-augmented Representation Generalization for Few-shot Action Recognition
Hongyu Qu, Ling Xing, Jiachao Zhang +3
Few-shot action recognition (FSAR) aims to recognize novel action categories with few exemplars. Existing methods typically learn frame-level representations for each video by desi…
Locality-aware Cross-modal Correspondence Learning for Dense Audio-Visual Events Localization
Ling Xing, Hongyu Qu, Rui Yan +2
Dense-localization Audio-Visual Events (DAVE) aims to identify time boundaries and corresponding categories for events that are both audible and visible in a long video, where even…
MVP-Shot: Multi-Velocity Progressive-Alignment Framework for Few-Shot Action Recognition
Hongyu Qu, Rui Yan, Xiangbo Shu +3
Recent few-shot action recognition (FSAR) methods typically perform semantic matching on learned discriminative features to achieve promising performance. However, most FSAR method…
Attack-Augmentation Mixing-Contrastive Skeletal Representation Learning
Binqian Xu, Xiangbo Shu, Jiachao Zhang +2
Contrastive learning, relying on effective positive and negative sample pairs, is beneficial to learn informative skeleton representations in unsupervised skeleton-based action rec…