5 citations · 6 across the 2 of their papers we have counts for
5 papers · 1 filter
TransFace++: Rethinking the Face Recognition Paradigm with a Focus on Accuracy, Efficiency, and Security
Jun Dan, Yang Liu, Baigui Sun +2
Face Recognition (FR) technology has made significant strides with the emergence of deep learning. Typically, most existing FR models are built upon Convolutional Neural Networks (…
Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
Yang Liu, Muzhi Zhu, Hengtao Li +3
Powered by large-scale pre-training, vision foundation models exhibit significant potential in open-world image understanding. However, unlike large language models that excel at d…
AutoTaskFormer: Searching Vision Transformers for Multi-task Learning
Yang Liu, Shen Yan, Yuge Zhang +5
Vision Transformers have shown great performance in single tasks such as classification and segmentation. However, real-world problems are not isolated, which calls for vision tran…
CLRNet: Cross Layer Refinement Network for Lane Detection
Tu Zheng, Yifei Huang, Yang Liu +4
Lane is critical in the vision navigation system of the intelligent vehicle. Naturally, lane is a traffic sign with high-level semantics, whereas it owns the specific local pattern…
DMN4: Few-shot Learning via Discriminative Mutual Nearest Neighbor Neural Network
Yang Liu, Tu Zheng, Jie Song +2
Few-shot learning (FSL) aims to classify images under low-data regimes, where the conventional pooled global feature is likely to lose useful local characteristics. Recent work has…