45 citations · 89 across the 17 of their papers we have counts for
17 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…
AdaFPP: Adapt-Focused Bi-Propagating Prototype Learning for Panoramic Activity Recognition
Meiqi Cao, Rui Yan, Xiangbo Shu +3
Panoramic Activity Recognition (PAR) aims to identify multi-granularity behaviors performed by multiple persons in panoramic scenes, including individual activities, group activiti…
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…
GPT4Ego: Unleashing the Potential of Pre-trained Models for Zero-Shot Egocentric Action Recognition
Guangzhao Dai, Xiangbo Shu, Wenhao Wu +2
Vision-Language Models (VLMs), pre-trained on large-scale datasets, have shown impressive performance in various visual recognition tasks. This advancement paves the way for notabl…
Boosting Weakly-Supervised Image Segmentation via Representation, Transform, and Compensator
Chunyan Wang, Dong Zhang, Rui Yan
Weakly-supervised image segmentation (WSIS) is a critical task in computer vision that relies on image-level class labels. Multi-stage training procedures have been widely used in…