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Article
Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors
Recent image-to-image (I2I) translation algorithms focus on learning the map** from a source to a target domain. However, the continuous translation problem that synthesizes intermediate results between two ...
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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
Regularizing Meta-learning via Gradient Dropout
With the growing attention on learning-to-learn new tasks using only a few examples, meta-learning has been widely used in numerous problems such as few-shot classification, reinforcement learning, and domain ...
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Article
DRIT++: Diverse Image-to-Image Translation via Disentangled Representations
Image-to-image translation aims to learn the map** between two visual domains. There are two main challenges for this task: (1) lack of aligned training pairs and (2) multiple possible outputs from a single ...
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Chapter and Conference Paper
RetrieveGAN: Image Synthesis via Differentiable Patch Retrieval
Image generation from scene description is a cornerstone technique for the controlled generation, which is beneficial to applications such as content creation and image editing. In this work, we aim to synthes...
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Chapter and Conference Paper
Modeling Artistic Workflows for Image Generation and Editing
People often create art by following an artistic workflow involving multiple stages that inform the overall design. If an artist wishes to modify an earlier decision, significant work may be required to propag...
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Chapter and Conference Paper
Semantic View Synthesis
We tackle a new problem of semantic view synthesis—generating free-viewpoint rendering of a synthesized scene using a semantic label map as input. We build upon recent advances in semantic image synthesis and ...
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Chapter and Conference Paper
Diverse Image-to-Image Translation via Disentangled Representations
Image-to-image translation aims to learn the map** between two visual domains. There are two main challenges for many applications: (1) the lack of aligned training pairs and (2) multiple possible outputs fr...
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Article
Geometry for Maximizing Localized Surface Plasmon Resonance of Au Nanorings with Random Orientations
The reduction of average extinction cross section of a localized surface plasmon (LSP) resonance mode under the random orientation condition of Au nanoring (NRI) distribution is first numerically demonstrated....
