Search Results for author:
Found 8 papers, 2 papers with code
HiFi4G: High-Fidelity Human Performance Rendering via Compact Gaussian Splatting
Then, we utilize a 4D Gaussian optimization scheme with adaptive spatial-temporal regularizers to effectively balance the non-rigid prior and Gaussian updating.
Instant-NVR: Instant Neural Volumetric Rendering for Human-object Interactions from Monocular RGBD Stream
We also provide an on-the-fly reconstruction scheme of the dynamic/static radiance fields via efficient motion-prior searching.
Human Performance Modeling and Rendering via Neural Animated Mesh
In this paper, we present a comprehensive neural approach for high-quality reconstruction, compression, and rendering of human performances from dense multi-view videos.
NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactions
In this paper, we propose NeuralHOFusion, a neural approach for volumetric human-object capture and rendering using sparse consumer RGBD sensors.
Artemis: Articulated Neural Pets with Appearance and Motion synthesis
Our ARTEMIS enables interactive motion control, real-time animation, and photo-realistic rendering of furry animals.
iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Rendering
To fill this gap, in this paper we propose a neural interactive bullet-time generator (iButter) for photo-realistic human free-viewpoint rendering from dense RGB streams, which enables flexible and interactive design for human bullet-time visual effects.
Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions
In this paper, we propose a neural human performance capture and rendering system to generate both high-quality geometry and photo-realistic texture of both human and objects under challenging interaction scenarios in arbitrary novel views, from only sparse RGB streams.
NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering using RGB Cameras
4D reconstruction and rendering of human activities is critical for immersive VR/AR experience. Recent advances still fail to recover fine geometry and texture results with the level of detail present in the input images from sparse multi-view RGB cameras.
