43 citations · 230 across the 21 of their papers we have counts for
6 papers · 1 filter
When Parameter-efficient Tuning Meets General-purpose Vision-language Models
Yihang Zhai, Haixin Wang, Jianlong Chang +4
Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate mul…
Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models
Lingxi Xie, Longhui Wei, Xiaopeng Zhang +4
The AI community has been pursuing algorithms known as artificial general intelligence (AGI) that apply to any kind of real-world problem. Recently, chat systems powered by large l…
Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
Haixin Wang, Xinlong Yang, Jianlong Chang +5
Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence. The c…
Visual Tuning
Bruce X. B. Yu, Jianlong Chang, Haixin Wang +9
Fine-tuning visual models has been widely shown promising performance on many downstream visual tasks. With the surprising development of pre-trained visual foundation models, visu…
LION: Implicit Vision Prompt Tuning
Haixin Wang, Jianlong Chang, Xiao Luo +3
Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs. Recently, vision prompt learning has pr…
Constraint and Union for Partially-Supervised Temporal Sentence Grounding
Chen Ju, Haicheng Wang, Jinxiang Liu +5
Temporal sentence grounding aims to detect the event timestamps described by the natural language query from given untrimmed videos. The existing fully-supervised setting achieves…