activity
20242026
collaborators

6 papers

cs.CV2026

Learning by Neighbor-Aware Semantics, Deciding by Open-form Flows: Towards Robust Zero-Shot Skeleton Action Recognition

Yang Chen, Miaoge Li, Zhijie Rao +3

Recognizing unseen skeleton action categories remains highly challenging due to the absence of corresponding skeletal priors. Existing approaches generally follow an ``align-then-c…

cs.LG2025

Semantic-guided LoRA Parameters Generation

Miaoge Li, Yang Chen, Zhijie Rao +2

Low-Rank Adaptation (LoRA) has demonstrated strong generalization capabilities across a variety of tasks for efficiently fine-tuning AI models, especially on resource-constrained e…

cs.CV2025

Exploring Transferable Homogeneous Groups for Compositional Zero-Shot Learning

Zhijie Rao, Jingcai Guo, Miaoge Li +1

Conditional dependency present one of the trickiest problems in Compositional Zero-Shot Learning, leading to significant property variations of the same state (object) across diffe…

cs.CV2024

On the Element-Wise Representation and Reasoning in Zero-Shot Image Recognition: A Systematic Survey

Jingcai Guo, Zhijie Rao, Zhi Chen +3

Zero-shot image recognition (ZSIR) aims to recognize and reason in unseen domains by learning generalized knowledge from limited data in the seen domain. The gist of ZSIR is constr…

cs.CV2024

Dual Expert Distillation Network for Generalized Zero-Shot Learning

Zhijie Rao, Jingcai Guo, Xiaocheng Lu +5

Zero-shot learning has consistently yielded remarkable progress via modeling nuanced one-to-one visual-attribute correlation. Existing studies resort to refining a uniform mapping…

cs.CV2024

Fine-Grained Zero-Shot Learning: Advances, Challenges, and Prospects

Jingcai Guo, Zhijie Rao, Zhi Chen +2

Recent zero-shot learning (ZSL) approaches have integrated fine-grained analysis, i.e., fine-grained ZSL, to mitigate the commonly known seen/unseen domain bias and misaligned visu…