307 citations · 624 across the 19 of their papers we have counts for
20 papers
Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation
Gang Li, Xiang Li, Yujie Wang +3
Knowledge Distillation (KD) is a widely-used technology to inherit information from cumbersome teacher models to compact student models, consequently realizing model compression an…
One to Transfer All: A Universal Transfer Framework for Vision Foundation Model with Few Data
Yujie Wang, Junqin Huang, Mengya Gao +4
The foundation model is not the last chapter of the model production pipeline. Transferring with few data in a general way to thousands of downstream tasks is becoming a trend of t…
INTERN: A New Learning Paradigm Towards General Vision
Jing Shao, Siyu Chen, Yangguang Li +24
Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society. However,…
Inter-class Discrepancy Alignment for Face Recognition
Jiaheng Liu, Yudong Wu, Yichao Wu +4
The field of face recognition (FR) has witnessed great progress with the surge of deep learning. Existing methods mainly focus on extracting discriminative features, and directly c…
Learning to Auto Weight: Entirely Data-driven and Highly Efficient Weighting Framework
Zhenmao Li, Yichao Wu, Ken Chen +4
Example weighting algorithm is an effective solution to the training bias problem, however, most previous typical methods are usually limited to human knowledge and require laborio…
Knowledge Distillation via Route Constrained Optimization
Xiao Jin, Baoyun Peng, Yichao Wu +5
Distillation-based learning boosts the performance of the miniaturized neural network based on the hypothesis that the representation of a teacher model can be used as structured a…