10 citations · 23 across the 15 of their papers we have counts for
4 papers · 1 filter
Video Diffusion Transformers are In-Context Learners
Zhengcong Fei, Di Qiu, Debang Li +2
This paper investigates a solution for enabling in-context capabilities of video diffusion transformers, with minimal tuning required for activation. Specifically, we propose a sim…
MovieCharacter: A Tuning-Free Framework for Controllable Character Video Synthesis
Di Qiu, Zheng Chen, Rui Wang +4
Recent advancements in character video synthesis still depend on extensive fine-tuning or complex 3D modeling processes, which can restrict accessibility and hinder real-time appli…
AdaFedFR: Federated Face Recognition with Adaptive Inter-Class Representation Learning
Di Qiu, Xinyang Lin, Kaiye Wang +2
With the growing attention on data privacy and communication security in face recognition applications, federated learning has been introduced to learn a face recognition model wit…
Learning from Imperfect Demonstrations with Self-Supervision for Robotic Manipulation
Kun Wu, Ning Liu, Zhen Zhao +5
Improving data utilization, especially for imperfect data from task failures, is crucial for robotic manipulation due to the challenging, time-consuming, and expensive data collect…