128 citations · 489 across the 27 of their papers we have counts for
5 papers · 1 filter
FTMoMamba: Motion Generation with Frequency and Text State Space Models
Chengjian Li, Xiangbo Shu, Qiongjie Cui +2
Diffusion models achieve impressive performance in human motion generation. However, current approaches typically ignore the significance of frequency-domain information in capturi…
EventCrab: Harnessing Frame and Point Synergy for Event-based Action Recognition and Beyond
Meiqi Cao, Xiangbo Shu, Jiachao Zhang +3
Event-based Action Recognition (EAR) possesses the advantages of high-temporal resolution capturing and privacy preservation compared with traditional action recognition. Current l…
FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data
Binqian Xu, Xiangbo Shu, Haiyang Mei +3
Multimodal Large Language Models (MLLMs) have made significant advancements, demonstrating powerful capabilities in processing and understanding multimodal data. Fine-tuning MLLMs…
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…