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Found 10 papers, 3 papers with code
GRIG: Few-Shot Generative Residual Image Inpainting
Image inpainting is the task of filling in missing or masked region of an image with semantically meaningful contents.
LPFF: A Portrait Dataset for Face Generators Across Large Poses
To better validate our pose-conditional 3D-aware generators, we develop a new FID measure to evaluate the 3D-level performance.
Real-time Controllable Motion Transition for Characters
Then, during generation, we design a transition model which is essentially a sampling strategy to sample from the learned manifold, based on the target frame and the aimed transition duration.
Parametric Reshaping of Portraits in Videos
In the second stage, we first reshape the reconstructed 3D face using a parametric reshaping model reflecting the weight change of the face, and then utilize the reshaped 3D face to guide the warping of video frames.
Predicting Loose-Fitting Garment Deformations Using Bone-Driven Motion Networks
We present a learning algorithm that uses bone-driven motion networks to predict the deformation of loose-fitting garment meshes at interactive rates.
Do Inpainting Yourself: Generative Facial Inpainting Guided by Exemplars
We introduce a novel attribute similarity metric to encourage networks to learn the style of facial attributes from the exemplar in a self-supervised way.
HairMapper: Removing Hair From Portraits Using GANs
Removing hair from portrait images is challenging due to the complex occlusions between hair and face, as well as the lack of paired portrait data with/without hair.
Example-based Real-time Clothing Synthesis for Virtual Agents
Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points.
Graphics
Progressive Feature Polishing Network for Salient Object Detection
Feature matters for salient object detection.
Quadruplet Network with One-Shot Learning for Fast Visual Object Tracking
In this paper, we propose a new quadruplet deep network to examine the potential connections among the training instances, aiming to achieve a more powerful representation.
