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Found 13 papers, 6 papers with code
NECA: Neural Customizable Human Avatar
The core of our approach is to represent humans in complementary dual spaces and predict disentangled neural fields of geometry, albedo, shadow, as well as an external lighting, from which we are able to derive realistic rendering with high-frequency details via volumetric rendering.
Template-Free Single-View 3D Human Digitalization with Diffusion-Guided LRM
We present Human-LRM, a diffusion-guided feed-forward model that predicts the implicit field of a human from a single image.
ActAnywhere: Subject-Aware Video Background Generation
Generating video background that tailors to foreground subject motion is an important problem for the movie industry and visual effects community.
Exploration of Adolescent Depression Risk Prediction Based on Census Surveys and General Life Issues
We introduced a method for managing severely imbalanced high-dimensional data and an adaptive predictive approach tailored to data structure characteristics.
Morig: Motion-aware rigging of character meshes from point clouds
We present MoRig, a method that automatically rigs character meshes driven by single-view point cloud streams capturing the motion of performing characters.
APES: Articulated Part Extraction from Sprite Sheets
Rigged puppets are one of the most prevalent representations to create 2D character animations.
Spatial-Temporal Residual Aggregation for High Resolution Video Inpainting
Recent learning-based inpainting algorithms have achieved compelling results for completing missing regions after removing undesired objects in videos.
International Workshop on Continual Semi-Supervised Learning: Introduction, Benchmarks and Baselines
The aim of this paper is to formalize a new continual semi-supervised learning (CSSL) paradigm, proposed to the attention of the machine learning community via the IJCAI 2021 International Workshop on Continual Semi-Supervised Learning (CSSL-IJCAI), with the aim of raising field awareness about this problem and mobilizing its effort in this direction.
Animating Through Warping: an Efficient Method for High-Quality Facial Expression Animation
It only requires the generator to be trained on small images and can do inference on an image of any size.
Contextual Residual Aggregation for Ultra High-Resolution Image Inpainting
Since convolutional layers of the neural network only need to operate on low-resolution inputs and outputs, the cost of memory and computing power is thus well suppressed.
Ranked #6 on
Image Inpainting
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RigNet: Neural Rigging for Articulated Characters
We present RigNet, an end-to-end automated method for producing animation rigs from input character models.
Predicting Animation Skeletons for 3D Articulated Models via Volumetric Nets
We present a learning method for predicting animation skeletons for input 3D models of articulated characters.
VisemeNet: Audio-Driven Animator-Centric Speech Animation
We present a novel deep-learning based approach to producing animator-centric speech motion curves that drive a JALI or standard FACS-based production face-rig, directly from input audio.
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