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Found 21 papers, 11 papers with code
Emerging Artificial Intelligence Applications in Spatial Transcriptomics Analysis
Spatial transcriptomics (ST) has advanced significantly in the last few years.
Computational Methods for Single-Cell Multi-Omics Integration and Alignment
Recently developed technologies to generate single-cell genomic data have made a revolutionary impact in the field of biology.
Collaging Class-specific GANs for Semantic Image Synthesis
We propose a new approach for high resolution semantic image synthesis.
IMAGINE: Image Synthesis by Image-Guided Model Inversion
We introduce an inversion based method, denoted as IMAge-Guided model INvErsion (IMAGINE), to generate high-quality and diverse images from only a single training sample.
Few-shot Image Generation via Cross-domain Correspondence
Training generative models, such as GANs, on a target domain containing limited examples (e. g., 10) can easily result in overfitting.
Rethinking and Improving the Robustness of Image Style Transfer
Extensive research in neural style transfer methods has shown that the correlation between features extracted by a pre-trained VGG network has a remarkable ability to capture the visual style of an image.
Content-Aware GAN Compression
We then propose a novel content-aware method to guide the processes of both pruning and distillation.
Neural Partial Differential Equations with Functional Convolution
Identifying the underlying structures of a PDE system based upon a small set of data samples on the solution space is challenging for machine learning.
Few-shot Image Generation with Elastic Weight Consolidation
Few-shot image generation seeks to generate more data of a given domain, with only few available training examples.
Learning to Caricature via Semantic Shape Transform
Caricature is an artistic drawing created to abstract or exaggerate facial features of a person.
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.
Collaborative Distillation for Ultra-Resolution Universal Style Transfer
In this work, we present a new knowledge distillation method (named Collaborative Distillation) for encoder-decoder based neural style transfer to reduce the convolutional filters.
Controllable and Progressive Image Extrapolation
Image extrapolation aims at expanding the narrow field of view of a given image patch.
Im2Pencil: Controllable Pencil Illustration from Photographs
We propose a high-quality photo-to-pencil translation method with fine-grained control over the drawing style.
Flow-Grounded Spatial-Temporal Video Prediction from Still Images
Existing video prediction methods mainly rely on observing multiple historical frames or focus on predicting the next one-frame.
A Closed-form Solution to Photorealistic Image Stylization
Photorealistic image stylization concerns transferring style of a reference photo to a content photo with the constraint that the stylized photo should remain photorealistic.
Joint Image Filtering with Deep Convolutional Networks
In contrast to existing methods that consider only the guidance image, the proposed algorithm can selectively transfer salient structures that are consistent with both guidance and target images.
Universal Style Transfer via Feature Transforms
The whitening and coloring transforms reflect a direct matching of feature covariance of the content image to a given style image, which shares similar spirits with the optimization of Gram matrix based cost in neural style transfer.
Generative Face Completion
In this paper, we propose an effective face completion algorithm using a deep generative model.
Diversified Texture Synthesis with Feed-forward Networks
Recent progresses on deep discriminative and generative modeling have shown promising results on texture synthesis.
Robust High Quality Image Guided Depth Upsampling
A popular solution is upsampling the obtained noisy low resolution depth map with the guidance of the companion high resolution color image.
