20 citations · 26 across the 4 of their papers we have counts for
4 papers
Supervised Fine-tuning in turn Improves Visual Foundation Models
Xiaohu Jiang, Yixiao Ge, Yuying Ge +3
Image-text training like CLIP has dominated the pretraining of vision foundation models in recent years. Subsequent efforts have been made to introduce region-level visual learning…
Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks
Hao Li, Jinguo Zhu, Xiaohu Jiang +8
Despite the remarkable success of foundation models, their task-specific fine-tuning paradigm makes them inconsistent with the goal of general perception modeling. The key to elimi…
Focal and Global Knowledge Distillation for Detectors
Zhendong Yang, Zhe Li, Xiaohu Jiang +4
Knowledge distillation has been applied to image classification successfully. However, object detection is much more sophisticated and most knowledge distillation methods have fail…
Guiding Query Position and Performing Similar Attention for Transformer-Based Detection Heads
Xiaohu Jiang, Ze Chen, Zhicheng Wang +2
After DETR was proposed, this novel transformer-based detection paradigm which performs several cross-attentions between object queries and feature maps for predictions has subsequ…