Search Results for author:
Found 7 papers, 6 papers with code
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
We introduce an efficient neural representation that, for the first time, enables real-time rendering of high-fidelity neural SDFs, while achieving state-of-the-art geometry reconstruction quality.
Variable Bitrate Neural Fields
Neural approximations of scalar and vector fields, such as signed distance functions and radiance fields, have emerged as accurate, high-quality representations.
A Dataset and Explorer for 3D Signed Distance Functions
Reference datasets are a key tool in the creation of new algorithms.
Learning Deformable Tetrahedral Meshes for 3D Reconstruction
We introduce Deformable Tetrahedral Meshes (DefTet) as a particular parameterization that utilizes volumetric tetrahedral meshes for the reconstruction problem.
AdaptNet: Policy Adaptation for Physics-Based Character Control
The technique is shown to be effective for adapting existing physics-based controllers to a wide range of new styles for locomotion, new task targets, changes in character morphology and extensive changes in environment.
Learning When to Speak: Latency and Quality Trade-offs for Simultaneous Speech-to-Speech Translation with Offline Models
Recent work in speech-to-speech translation (S2ST) has focused primarily on offline settings, where the full input utterance is available before any output is given.
Robust Vision-Based Cheat Detection in Competitive Gaming
Game publishers and anti-cheat companies have been unsuccessful in blocking cheating in online gaming.
