6 citations · 6 across the 5 of their papers we have counts for
5 papers
MLLM-DataEngine: Closing the Loop of Multimodal Instruction Tuning Data Generation
Zhiyuan Zhao, Bin Wang, Linke Ouyang +5
In this paper, we propose MLLM-DataEngine, a novel closed-loop system that bridges data generation, model training, and evaluation. Within each loop iteration, the MLLM-DataEngine…
Parrot Captions Teach CLIP to Spot Text
Yiqi Lin, Conghui He, Alex Jinpeng Wang +3
Despite CLIP being the foundation model in numerous vision-language applications, the CLIP suffers from a severe text spotting bias. Such bias causes CLIP models to `Parrot' the vi…
SEPT: Towards Scalable and Efficient Visual Pre-Training
Yiqi Lin, Huabin Zheng, Huaping Zhong +4
Recently, the self-supervised pre-training paradigm has shown great potential in leveraging large-scale unlabeled data to improve downstream task performance. However, increasing t…
MINI: Mining Implicit Novel Instances for Few-Shot Object Detection
Yuhang Cao, Jiaqi Wang, Yiqi Lin +1
Learning from a few training samples is a desirable ability of an object detector, inspiring the explorations of Few-Shot Object Detection (FSOD). Most existing approaches employ a…
Exploring the Interactive Guidance for Unified and Effective Image Matting
Dinghao Yang, Bin Wang, Weijia Li +2
Recent image matting studies are developing towards proposing trimap-free or interactive methods for complete complex image matting tasks. Although avoiding the extensive labors of…