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Chapter and Conference Paper
Revisiting TENT for Test-Time Adaption Semantic Segmentation and Classification Head Adjustment
Test-time adaption is very effective at solving the domain shift problem where the training data and testing data are sampled from different domains. However, most test-time adaption methods made their success...
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Chapter and Conference Paper
Enhancing Adversarial Transferability from the Perspective of Input Loss Landscape
The transferability of adversarial examples enables the black-box attacks and poses a threat to the application of deep neural networks in real-world, which has attracted great attention in recent years. Regar...
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Chapter and Conference Paper
HTCN: Harmonious Text Colorization Network for Visual-Textual Presentation Design
The selection of text color is a time-consuming and important aspect in the designing of visual-textual presentation layout. In this paper, we propose a novel deep neural network architecture for predicting te...
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Chapter and Conference Paper
Talking Face Video Generation with Editable Expression
In rencent years, the convolutional neural network have been proved to be a great success in generating talking face. Existing methods have combined a single face image with speech to generate talking face vid...
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Chapter and Conference Paper
Towards More Powerful Multi-column Convolutional Network for Crowd Counting
Scale variation has always been one of the most challenging problems for crowd counting. By using multi-column convolutions with different receptive fields to deal with different scales in the scene, the multi...
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Chapter and Conference Paper
Stereo Visual SLAM Using Bag of Point and Line Word Pairs
The traditional point-based SLAM algorithm performs poorly due to light changing, low-texture and highly similar scenes, while line segment features can better describe the structural information of the enviro...