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Chapter and Conference Paper
Vector Quantized Image-to-Image Translation
Current image-to-image translation methods formulate the task with conditional generation models, leading to learning only the recolorization or regional changes as being constrained by the rich structural inf...
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Chapter and Conference Paper
3D-PL: Domain Adaptive Depth Estimation with 3D-Aware Pseudo-Labeling
For monocular depth estimation, acquiring ground truths for real data is not easy, and thus domain adaptation methods are commonly adopted using the supervised synthetic data. However, this may still incur a l...
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Chapter and Conference Paper
Demystifying T1-MRI to FDG \(^{18}\) -PET Image Translation via Representational Similarity
Recent development of image-to-image translation techniques has enabled the generation of rare medical images (e.g., PET) from common ones (e.g., MRI). Beyond the potential benefits of the reduction in scannin...
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Chapter and Conference Paper
Class-Incremental Learning with Rectified Feature-Graph Preservation
In this paper, we address the problem of distillation-based class-incremental learning with a single head. A central theme of this task is to learn new classes that arrive in sequential phases over time while ...
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Chapter and Conference Paper
Colorization of Depth Map via Disentanglement
Vision perception is one of the most important components for a computer or robot to understand the surrounding scene and achieve autonomous applications. However, most of the vision models are based on the ...
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Chapter and Conference Paper
Summarizing First-Person Videos from Third Persons’ Points of Views
Video highlight or summarization is among interesting topics in computer vision, which benefits a variety of applications like viewing, searching, or storage. However, most existing studies rely on training da...
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Chapter and Conference Paper
Towards Segmenting Consumer Stereo Videos: Benchmark, Baselines and Ensembles
Are we ready to segment consumer stereo videos? The amount of this data type is rapidly increasing and encompasses rich information of appearance, motion and depth cues. However, the segmentation of such data is ...
