6 citations · 7 across the 12 of their papers we have counts for
6 papers · 1 filter
Revisiting Cross-Architecture Distillation: Adaptive Dual-Teacher Transfer for Lightweight Video Models
Ying Peng, Hongsen Ye, Changxin Huang +3
Vision Transformers (ViTs) have achieved strong performance in video action recognition, but their high computational cost limits their practicality. Lightweight CNNs are more effi…
A Byzantine-Robust Federated Learning with Nesterov Momentum
Lihan Xu, Xiaoyi Fan, Gang Wang +3
We investigate robust federated learning, where a group of workers collaboratively train a shared model under the orchestration of a central server in the presence of Byzantine adv…
CO-PFL: Contribution-Oriented Personalized Federated Learning for Heterogeneous Networks
Ke Xing, Yanjie Dong, Xiaoyi Fan +4
Personalized federated learning (PFL) addresses a critical challenge of collaboratively training customized models for clients with heterogeneous and scarce local data. Conventiona…
OVG-HQ: Online Video Grounding with Hybrid-modal Queries
Runhao Zeng, Jiaqi Mao, Minghao Lai +5
Video grounding (VG) task focuses on locating specific moments in a video based on a query, usually in text form. However, traditional VG struggles with some scenarios like streami…
Emotion Recognition from Skeleton Data: A Comprehensive Survey
Haifeng Lu, Jiuyi Chen, Zhen Zhang +3
Emotion recognition through body movements has emerged as a compelling and privacy-preserving alternative to traditional methods that rely on facial expressions or physiological si…
Exploring Audio Cues for Enhanced Test-Time Video Model Adaptation
Runhao Zeng, Qi Deng, Ronghao Zhang +4
Test-time adaptation (TTA) aims to boost the generalization capability of a trained model by conducting self-/unsupervised learning during the testing phase. While most existing TT…