3 citations · 5 across the 3 of their papers we have counts for
3 papers
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Haiyang Wang, Hao Tang, Li Jiang +5
This paper proposes a simple, yet effective framework, called GiT, simultaneously applicable for various vision tasks only with a vanilla ViT. Motivated by the universality of the…
Learning to Prompt with Text Only Supervision for Vision-Language Models
Muhammad Uzair Khattak, Muhammad Ferjad Naeem, Muzammal Naseer +2
Foundational vision-language models such as CLIP are becoming a new paradigm in vision, due to their excellent generalization abilities. However, adapting these models for downstre…
Introducing Language Guidance in Prompt-based Continual Learning
Muhammad Gul Zain Ali Khan, Muhammad Ferjad Naeem, Luc Van Gool +3
Continual Learning aims to learn a single model on a sequence of tasks without having access to data from previous tasks. The biggest challenge in the domain still remains catastro…