Search Results for author:
Found 25 papers, 9 papers with code
Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks
The Graph Convolutional Networks (GCNs) have achieved excellent results in node classification tasks, but the model's performance at low label rates is still unsatisfactory.
Unsupervised Image-to-Image Translation with Generative Prior
In this work, we present a novel framework, Generative Prior-guided UNsupervised Image-to-image Translation (GP-UNIT), to improve the overall quality and applicability of the translation algorithm.
Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer
Recent studies on StyleGAN show high performance on artistic portrait generation by transfer learning with limited data.
ShapeEditer: a StyleGAN Encoder for Face Swapping
In this paper, we propose a novel encoder, called ShapeEditor, for high-resolution, realistic and high-fidelity face exchange.
Boosting-GNN: Boosting Algorithm for Graph Networks on Imbalanced Node Classification
Traditional methods such as resampling, reweighting, and synthetic samples that deal with imbalanced datasets are no longer applicable in GNN.
Towards Efficient Local Causal Structure Learning
Local causal structure learning aims to discover and distinguish direct causes (parents) and direct effects (children) of a variable of interest from data.
Learning causal representations for robust domain adaptation
In this paper, we study the cases where at the training phase the target domain data is unavailable and only well-labeled source domain data is available, called robust domain adaptation.
Consistent Video Style Transfer via Relaxation and Regularization
In this article, we address the problem by jointly considering the intrinsic properties of stylization and temporal consistency.
Open Benchmarking for Click-Through Rate Prediction
We have publicly released the benchmarking code, evaluation protocols, and experimental settings of our work to promote reproducible research in this field.
New opportunities at the photon energy frontier
Ultra-peripheral collisions (UPCs) involving heavy ions and protons are the energy frontier for photon-mediated interactions.
High Energy Physics - Phenomenology High Energy Physics - Experiment Nuclear Experiment
From Design Draft to Real Attire: Unaligned Fashion Image Translation
Moreover, built upon the sampling network, we present design draft to real fashion item translation network (D2RNet), where two separate translation streams that focus on texture and shape, respectively, are combined tactfully to get both benefits.
Towards Coding for Human and Machine Vision: A Scalable Image Coding Approach
In this paper, we come up with a novel image coding framework by leveraging both the compressive and the generative models, to support machine vision and human perception tasks jointly.
Deep Plastic Surgery: Robust and Controllable Image Editing with Human-Drawn Sketches
We present a sketch refinement strategy, as inspired by the coarse-to-fine drawing process of the artists, which we show can help our model well adapt to casual and varied sketches without the need for real sketch training data.
Residual Encoder-Decoder Network for Deep Subspace Clustering
Subspace clustering aims to cluster unlabeled data that lies in a union of low-dimensional linear subspaces.
Towards Efficient Local Causal Structure Learning
To tackle this issue, we propose a novel Efficient Local Causal Structure learning algorithm, named ELCS.
Semi-supervised representation learning via dual autoencoders for domain adaptation
Domain adaptation aims to exploit the knowledge in source domain to promote the learning tasks in target domain, which plays a critical role in real-world applications.
TE141K: Artistic Text Benchmark for Text Effect Transfer
To the best of our knowledge, this is the largest dataset for text effect transfer to date.
Controllable Artistic Text Style Transfer via Shape-Matching GAN
In this paper, we present the first text style transfer network that allows for real-time control of the crucial stylistic degree of the glyph through an adjustable parameter.
Three-Stage Subspace Clustering Framework with Graph-Based Transformation and Optimization
The affinity matrix is obtained in the first stage, then it goes through the second stage, where the proposed GBTO is applied to generate a reconstructed affinity matrix with more authentic similarity between data points.
Restricted Connection Orthogonal Matching Pursuit For Sparse Subspace Clustering
In this paper, we propose a noise-robust algorithm, Restricted Connection Orthogonal Matching Pursuit for Sparse Subspace Clustering (RCOMP-SSC), to improve the clustering accuracy and maintain the low computational time by restricting the number of connections of each data point during the iteration of OMP.
TET-GAN: Text Effects Transfer via Stylization and Destylization
The key idea is to train our network to accomplish both the objective of style transfer and style removal, so that it can learn to disentangle and recombine the content and style features of text effects images.
Context-Aware Text-Based Binary Image Stylization and Synthesis
The stylization is then followed by a context-aware layout design algorithm, where cues for both seamlessness and aesthetics are employed to determine the optimal layout of the shape in the background.
Erase or Fill? Deep Joint Recurrent Rain Removal and Reconstruction in Videos
In this paper, we address the problem of video rain removal by constructing deep recurrent convolutional networks.
Awesome Typography: Statistics-Based Text Effects Transfer
It allows our algorithm to produce artistic typography that fits for both local texture patterns and the global spatial distribution in the example.
