11 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
Zhengbo Wang, Jian Liang, Lijun Sheng +3
Contrastive Language-Image Pretraining (CLIP) has gained popularity for its remarkable zero-shot capacity. Recent research has focused on developing efficient fine-tuning methods,…
cs.CV2023★ 11 cited
Improving Zero-Shot Generalization for CLIP with Synthesized Prompts
Zhengbo Wang, Jian Liang, Ran He +3
With the growing interest in pretrained vision-language models like CLIP, recent research has focused on adapting these models to downstream tasks. Despite achieving promising resu…
cs.CV2023
Exploiting Semantic Attributes for Transductive Zero-Shot Learning
Zhengbo Wang, Jian Liang, Zilei Wang +1
Zero-shot learning (ZSL) aims to recognize unseen classes by generalizing the relation between visual features and semantic attributes learned from the seen classes. A recent parad…