5 papers
FACT: A Simple and Efficient Framework for Active Finetuning
Wenshuai Xu, You Song, Yuzhuo Cui +3
The main goal of active finetuning is to improve a pretrained model's performance on a specific task or domain by finetuning it with carefully selected informative or challenging d…
STDDN: A Physics-Guided Deep Learning Framework for Crowd Simulation
Zijin Liu, Xu Geng, Wenshuai Xu +3
Accurate crowd simulation is crucial for public safety management, emergency evacuation planning, and intelligent transportation systems. However, existing methods, which typically…
BSS-Bench: Towards Reproducible and Effective Band Selection Search
Wenshuai Xu, Zhenbo Xu
The key technology to overcome the drawbacks of hyperspectral imaging (expensive, high capture delay, and low spatial resolution) and make it widely applicable is to select only a…
ActiveDC: Distribution Calibration for Active Finetuning
Wenshuai Xu, Zhenghui Hu, Yu Lu +3
The pretraining-finetuning paradigm has gained popularity in various computer vision tasks. In this paradigm, the emergence of active finetuning arises due to the abundance of larg…
One-shot neural band selection for spectral recovery
Hai-Miao Hu, Zhenbo Xu, Wenshuai Xu +5
Band selection has a great impact on the spectral recovery quality. To solve this ill-posed inverse problem, most band selection methods adopt hand-crafted priors or exploit cluste…