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Found 8 papers, 3 papers with code
RSMT: Real-time Stylized Motion Transition for Characters
Styled online in-between motion generation has important application scenarios in computer animation and games.
FAIVConf: Face enhancement for AI-based Video Conference with Low Bit-rate
Recently, high-quality video conferencing with fewer transmission bits has become a very hot and challenging problem.
Online Meta Adaptation for Variable-Rate Learned Image Compression
This work addresses two major issues of end-to-end learned image compression (LIC) based on deep neural networks: variable-rate learning where separate networks are required to generate compressed images with varying qualities, and the train-test mismatch between differentiable approximate quantization and true hard quantization.
Efficient Micro-Structured Weight Unification and Pruning for Neural Network Compression
Compressing Deep Neural Network (DNN) models to alleviate the storage and computation requirements is essential for practical applications, especially for resource limited devices.
End-to-End Denoising of Dark Burst Images Using Recurrent Fully Convolutional Networks
When taking photos in dim-light environments, due to the small amount of light entering, the shot images are usually extremely dark, with a great deal of noise, and the color cannot reflect real-world color.
MVF-Net: Multi-View 3D Face Morphable Model Regression
The main ingredient of the view alignment loss is a differentiable dense optical flow estimator that can backpropagate the alignment errors between an input view and a synthetic rendering from another input view, which is projected to the target view through the 3D shape to be inferred.
SRDGAN: learning the noise prior for Super Resolution with Dual Generative Adversarial Networks
In this work, an end-to-end novel framework, including high-to-low network and low-to-high network, is proposed to solve the above problems with dual Generative Adversarial Networks (GAN).
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3D Facial Expression Reconstruction using Cascaded Regression
2D landmarks are detected and used to initialize the 3D shape and mapping matrices.
