52 citations · 85 across the 6 of their papers we have counts for
6 papers
SAM-Med2D
Junlong Cheng, Jin Ye, Zhongying Deng +12
The Segment Anything Model (SAM) represents a state-of-the-art research advancement in natural image segmentation, achieving impressive results with input prompts such as points an…
STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training
Ziyan Huang, Haoyu Wang, Zhongying Deng +8
Large-scale models pre-trained on large-scale datasets have profoundly advanced the development of deep learning. However, the state-of-the-art models for medical image segmentatio…
IntraLoss: Further Margin via Gradient-Enhancing Term for Deep Face Recognition
Chengzhi Jiang, Yanzhou Su, Wen Wang +3
Existing classification-based face recognition methods have achieved remarkable progress, introducing large margin into hypersphere manifold to learn discriminative facial represen…
TTPP: Temporal Transformer with Progressive Prediction for Efficient Action Anticipation
Wen Wang, Xiaojiang Peng, Yanzhou Su +2
Video action anticipation aims to predict future action categories from observed frames. Current state-of-the-art approaches mainly resort to recurrent neural networks to encode hi…
A Discriminative Learned CNN Embedding for Remote Sensing Image Scene Classification
Wen Wang, Lijun Du, Yinxing Gao +3
In this work, a discriminatively learned CNN embedding is proposed for remote sensing image scene classification. Our proposed siamese network simultaneously computes the classific…
The General Pair-based Weighting Loss for Deep Metric Learning
Haijun Liu, Jian Cheng, Wen Wang +1
Deep metric learning aims at learning the distance metric between pair of samples, through the deep neural networks to extract the semantic feature embeddings where similar samples…