2 citations · 7 across the 6 of their papers we have counts for
6 papers
DREAM+: Efficient Dataset Distillation by Bidirectional Representative Matching
Yanqing Liu, Jianyang Gu, Kai Wang +4
Dataset distillation plays a crucial role in creating compact datasets with similar training performance compared with original large-scale ones. This is essential for addressing t…
Can pre-trained models assist in dataset distillation?
Yao Lu, Xuguang Chen, Yuchen Zhang +7
Dataset Distillation (DD) is a prominent technique that encapsulates knowledge from a large-scale original dataset into a small synthetic dataset for efficient training. Meanwhile,…
Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification
Jianyang Gu, Hao Luo, Kai Wang +3
Unsupervised domain adaptive person re-identification (Re-ID) methods alleviate the burden of data annotation through generating pseudo supervision messages. However, real-world Re…
Dataset Quantization
Daquan Zhou, Kai Wang, Jianyang Gu +5
State-of-the-art deep neural networks are trained with large amounts (millions or even billions) of data. The expensive computation and memory costs make it difficult to train them…
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID
Jianyang Gu, Kai Wang, Hao Luo +6
Neural Architecture Search (NAS) has been increasingly appealing to the society of object Re-Identification (ReID), for that task-specific architectures significantly improve the r…
Dynamic Gradient Reactivation for Backward Compatible Person Re-identification
Xiao Pan, Hao Luo, Weihua Chen +6
We study the backward compatible problem for person re-identification (Re-ID), which aims to constrain the features of an updated new model to be comparable with the existing featu…