1 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
Neutral-Reference Prompting for Vision-Language Models
Senmao Tian, Xiang Wei, Shunli Zhang
Efficient transfer learning of vision-language models (VLMs) commonly suffers from a Base-New Trade-off (BNT): improving performance on unseen (new) classes often degrades accuracy…
GaitAdapt: Continual Learning for Evolving Gait Recognition
Jingjie Wang, Shunli Zhang, Xiang Wei +1
Current gait recognition methodologies generally necessitate retraining when encountering new datasets. Nevertheless, retrained models frequently encounter difficulties in preservi…
Accurate Quantization for Gait Representation Learning
S. Tian, H. Gao, G. Hong +4
Existing deep learning methods have made significant progress in gait representation learning. Quantization can facilitate the application of gait models as a model-agnostic genera…
Adaptive quantization with mixed-precision based on low-cost proxy
Junzhe Chen, Qiao Yang, Senmao Tian +1
It is critical to deploy complicated neural network models on hardware with limited resources. This paper proposes a novel model quantization method, named the Low-Cost Proxy-Based…
IAIFNet: An Illumination-Aware Infrared and Visible Image Fusion Network
Qiao Yang, Yu Zhang, Zijing Zhao +2
Infrared and visible image fusion (IVIF) is used to generate fusion images with comprehensive features of both images, which is beneficial for downstream vision tasks. However, cur…