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Found 18 papers, 6 papers with code
Quark: Real-time, High-resolution, and General Neural View Synthesis
Our feed-forward network generalizes across a wide variety of datasets and scenes and produces state-of-the-art quality for a real-time method.
Text2Immersion: Generative Immersive Scene with 3D Gaussians
We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts.
AlteredAvatar: Stylizing Dynamic 3D Avatars with Fast Style Adaptation
Among existing approaches for avatar stylization, direct optimization methods can produce excellent results for arbitrary styles but they are unpleasantly slow.
RelightableHands: Efficient Neural Relighting of Articulated Hand Models
To achieve generalization, we condition the student model with physics-inspired illumination features such as visibility, diffuse shading, and specular reflections computed on a coarse proxy geometry, maintaining a small computational overhead.
MEGANE: Morphable Eyeglass and Avatar Network
However, modeling the geometric and appearance interactions of glasses and the face of virtual representations of humans is challenging.
NeuWigs: A Neural Dynamic Model for Volumetric Hair Capture and Animation
The capture and animation of human hair are two of the major challenges in the creation of realistic avatars for the virtual reality.
Multiface: A Dataset for Neural Face Rendering
Along with the release of the dataset, we conduct ablation studies on the influence of different model architectures toward the model's interpolation capacity of novel viewpoint and expressions.
HVH: Learning a Hybrid Neural Volumetric Representation for Dynamic Hair Performance Capture
Capturing and rendering life-like hair is particularly challenging due to its fine geometric structure, the complex physical interaction and its non-trivial visual appearance. Yet, hair is a critical component for believable avatars.
Advances in Neural Rendering
The reconstruction of such a scene representation from observations using differentiable rendering losses is known as inverse graphics or inverse rendering.
Pixel-Aligned Volumetric Avatars
Volumetric models typically employ a global code to represent facial expressions, such that they can be driven by a small set of animation parameters.
Ranked #5 on
Generalizable Novel View Synthesis
on ZJU-MoCap
Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality
Social presence, the feeling of being there with a real person, will fuel the next generation of communication systems driven by digital humans in virtual reality (VR).
Mixture of Volumetric Primitives for Efficient Neural Rendering
Real-time rendering and animation of humans is a core function in games, movies, and telepresence applications.
PVA: Pixel-aligned Volumetric Avatars
Volumetric models typically employ a global code to represent facial expressions, such that they can be driven by a small set of animation parameters.
Learning Compositional Radiance Fields of Dynamic Human Heads
In addition, we show that the learned dynamic radiance field can be used to synthesize novel unseen expressions based on a global animation code.
State of the Art on Neural Rendering
Neural rendering is a new and rapidly emerging field that combines generative machine learning techniques with physical knowledge from computer graphics, e. g., by the integration of differentiable rendering into network training.
Neural Volumes: Learning Dynamic Renderable Volumes from Images
Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occlusion, and biological motion.
Deep Appearance Models for Face Rendering
At inference time, we condition the decoding network on the viewpoint of the camera in order to generate the appropriate texture for rendering.
Radiometric Scene Decomposition: Scene Reflectance, Illumination, and Geometry from RGB-D Images
Recovering the radiometric properties of a scene (i. e., the reflectance, illumination, and geometry) is a long-sought ability of computer vision that can provide invaluable information for a wide range of applications.
