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With the success of the DEtection TRansformer (DETR), numerous researchers have explored its effectiveness in addressing unsupervised domain adaptation tasks. Existing methods leverage carefully designed feature alignment techniques to align the backbone ...

Semantic segmentation of remote sensing images aims to achieve pixel-level semantic category assignment for input images. This task has achieved significant advances with the rapid development of deep neural network. Most current methods mainly focus on ...

With the increasing popularity of learning Chinese as a second language (L2), the development of an automated essay scoring (AES) method specially for Chinese L2 essays has become an important task. To build a robust model that could easily adapt ...

Edge detection has made significant progress with the help of deep convolutional networks (ConvNet). These ConvNet-based edge detectors have approached human level performance on standard benchmarks. We provide a systematical study of these detectors&#...

Shadow detection is an important and challenging problem in computer vision. Recently, single image shadow detection had achieved major progress with the development of deep convolutional networks. However, existing methods are still vulnerable to ...