152 citations · 214 across the 10 of their papers we have counts for
5 papers · 1 filter
Conditional Representation Learning for Customized Tasks
Honglin Liu, Chao Sun, Peng Hu +2
Conventional representation learning methods learn a universal representation that primarily captures dominant semantics, which may not always align with customized downstream task…
DUDE: Diffusion-Based Unsupervised Cross-Domain Image Retrieval
Ruohong Yang, Peng Hu, Yunfan Li +1
Unsupervised cross-domain image retrieval (UCIR) aims to retrieve images of the same category across diverse domains without relying on annotations. Existing UCIR methods, which al…
DiFiC: Your Diffusion Model Holds the Secret to Fine-Grained Clustering
Ruohong Yang, Peng Hu, Xi Peng +2
Fine-grained clustering is a practical yet challenging task, whose essence lies in capturing the subtle differences between instances of different classes. Such subtle differences…
A Survey on Deep Clustering: From the Prior Perspective
Yiding Lu, Haobin Li, Yunfan Li +2
Facilitated by the powerful feature extraction ability of neural networks, deep clustering has achieved great success in analyzing high-dimensional and complex real-world data. The…
An Empirical Study of Parameter Efficient Fine-tuning on Vision-Language Pre-train Model
Yuxin Tian, Mouxing Yang, Yunfan Li +4
Recent studies applied Parameter Efficient Fine-Tuning techniques (PEFTs) to efficiently narrow the performance gap between pre-training and downstream. There are two important fac…