22 citations · 27 across the 7 of their papers we have counts for
7 papers
Dynamic Low-Resolution Distillation for Cost-Efficient End-to-End Text Spotting
Ying Chen, Liang Qiao, Zhanzhan Cheng +3
End-to-end text spotting has attached great attention recently due to its benefits on global optimization and high maintainability for real applications. However, the input scale h…
Bias-Eliminated Semantic Refinement for Any-Shot Learning
Liangjun Feng, Chunhui Zhao, Xi Li
When training samples are scarce, the semantic embedding technique, ie, describing class labels with attributes, provides a condition to generate visual features for unseen objects…
Dual-Tasks Siamese Transformer Framework for Building Damage Assessment
Hongruixuan Chen, Edoardo Nemni, Sofia Vallecorsa +3
Accurate and fine-grained information about the extent of damage to buildings is essential for humanitarian relief and disaster response. However, as the most commonly used archite…
Learning to Generate Content-Aware Dynamic Detectors
Junyi Feng, Jiashen Hua, Baisheng Lai +3
Model efficiency is crucial for object detection. Mostprevious works rely on either hand-crafted design or auto-search methods to obtain a static architecture, regardless ofthe dif…
A Multi-Semantic Metapath Model for Large Scale Heterogeneous Network Representation Learning
Xuandong Zhao, Jinbao Xue, Jin Yu +2
Network Embedding has been widely studied to model and manage data in a variety of real-world applications. However, most existing works focus on networks with single-typed nodes o…
DR-Net: Transmission Steered Single Image Dehazing Network with Weakly Supervised Refinement
Chongyi Li, Jichang Guo, Fatih Porikli +3
Despite the recent progress in image dehazing, several problems remain largely unsolved such as robustness for varying scenes, the visual quality of reconstructed images, and effec…