7 citations · 12 across the 10 of their papers we have counts for
5 papers · 1 filter
Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot Learning
Xiaocheng Lu, Ziming Liu, Song Guo +1
Compositional Zero-Shot Learning (CZSL) aims to recognize novel concepts formed by known states and objects during training. Existing methods either learn the combined state-object…
ProCC: Progressive Cross-primitive Compatibility for Open-World Compositional Zero-Shot Learning
Fushuo Huo, Wenchao Xu, Song Guo +4
Open-World Compositional Zero-shot Learning (OW-CZSL) aims to recognize novel compositions of state and object primitives in images with no priors on the compositional space, which…
Fed-FSNet: Mitigating Non-I.I.D. Federated Learning via Fuzzy Synthesizing Network
Jingcai Guo, Song Guo, Jie Zhang +1
Federated learning (FL) has emerged as a promising privacy-preserving distributed machine learning framework recently. It aims at collaboratively learning a shared global model by…
Anchor Sampling for Federated Learning with Partial Client Participation
Feijie Wu, Song Guo, Zhihao Qu +3
Compared with full client participation, partial client participation is a more practical scenario in federated learning, but it may amplify some challenges in federated learning,…
Towards Unbiased Multi-label Zero-Shot Learning with Pyramid and Semantic Attention
Ziming Liu, Song Guo, Jingcai Guo +2
Multi-label zero-shot learning extends conventional single-label zero-shot learning to a more realistic scenario that aims at recognizing multiple unseen labels of classes for each…