1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2025
EPIPTrack: Rethinking Prompt Modeling with Explicit and Implicit Prompts for Multi-Object Tracking
Yukuan Zhang, Jiarui Zhao, Shangqing Nie +2
Multimodal semantic cues, such as textual descriptions, have shown strong potential in enhancing target perception for tracking. However, existing methods rely on static textual de…
cs.CV2024
Training-Free Unsupervised Prompt for Vision-Language Models
Sifan Long, Linbin Wang, Zhen Zhao +4
Prompt learning has become the most effective paradigm for adapting large pre-trained vision-language models (VLMs) to downstream tasks. Recently, unsupervised prompt tuning method…
cs.CV2023★ 1 cited
Task-Oriented Multi-Modal Mutual Leaning for Vision-Language Models
Sifan Long, Zhen Zhao, Junkun Yuan +5
Prompt learning has become one of the most efficient paradigms for adapting large pre-trained vision-language models to downstream tasks. Current state-of-the-art methods, like CoO…