Search Results for author:
Found 7 papers, 4 papers with code
LoopAnimate: Loopable Salient Object Animation
The proposed LoopAnimate, which for the first time extends the single-pass generation length of UNet-based video generation models to 35 frames while maintaining high-quality video generation.
u-LLaVA: Unifying Multi-Modal Tasks via Large Language Model
Recent advancements in multi-modal large language models (MLLMs) have led to substantial improvements in visual understanding, primarily driven by sophisticated modality alignment strategies.
CLIP Brings Better Features to Visual Aesthetics Learners
Specifically, we first integrate and leverage a multi-source unlabeled dataset to align rich features between a given visual encoder and an off-the-shelf CLIP image encoder via feature alignment loss.
A Federated Data-Driven Evolutionary Algorithm for Expensive Multi/Many-objective Optimization
Data-driven optimization has found many successful applications in the real world and received increased attention in the field of evolutionary optimization.
Federated Learning on Non-IID Data: A Survey
Federated learning is an emerging distributed machine learning framework for privacy preservation.
A Federated Data-Driven Evolutionary Algorithm
Data-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems.
Ternary Compression for Communication-Efficient Federated Learning
Learning over massive data stored in different locations is essential in many real-world applications.
