3 papers
cs.CV2025
AnchorOPT: Towards Optimizing Dynamic Anchors for Adaptive Prompt Learning
Zheng Li, Yibing Song, Xin Zhang +3
Existing prompt learning methods, which are built upon CLIP models, leverage textual tokens as anchors to guide the learnable soft tokens. This guidance improves CLIP generalizatio…
cs.CV2025
Re-Aligning Language to Visual Objects with an Agentic Workflow
Yuming Chen, Jiangyan Feng, Haodong Zhang +6
Language-based object detection (LOD) aims to align visual objects with language expressions. A large amount of paired data is utilized to improve LOD model generalizations. During…
cs.CV2024
Advancing Textual Prompt Learning with Anchored Attributes
Zheng Li, Yibing Song, Ming-Ming Cheng +2
Textual-based prompt learning methods primarily employ multiple learnable soft prompts and hard class tokens in a cascading manner as text inputs, aiming to align image and text (c…