Search Results for author:
Found 11 papers, 5 papers with code
SketchMetaFace: A Learning-based Sketching Interface for High-fidelity 3D Character Face Modeling
User studies demonstrate the superiority of our system over existing modeling tools in terms of the ease to use and visual quality of results.
3D Keypoint Estimation Using Implicit Representation Learning
Inspired by the recent success of advanced implicit representation in reconstruction tasks, we explore the idea of using an implicit field to represent keypoints.
NerVE: Neural Volumetric Edges for Parametric Curve Extraction from Point Cloud
We show that a simple network based on NerVE can already outperform the previous state-of-the-art methods by a great margin.
PIFu for the Real World: A Self-supervised Framework to Reconstruct Dressed Human from Single-view Images
On synthetic data, our Intersection-Over-Union (IoU) achieves to 93. 5%, 18% higher compared with PIFuHD.
SimpModeling: Sketching Implicit Field to Guide Mesh Modeling for 3D Animalmorphic Head Design
In this work, we propose SimpModeling, a novel sketch-based system for helping users, especially amateur users, easily model 3D animalmorphic heads - a prevalent kind of heads in character design.
Scalable Memory Protection in the PENGLAI Enclave
Upon these two primitives, our system can scale to thousands of concurrent enclaves with high resource utilization and eliminate the high-cost initialization of secure memory using fork-style enclave creation without weakening the security guarantees.
Characterizing serverless platforms with serverlessbench
This, however, also presents new challenges including how to efficiently design high-performance serverless platforms and how to efficiently program on the platforms.
Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images
High-fidelity clothing reconstruction is the key to achieving photorealism in a wide range of applications including human digitization, virtual try-on, etc.
FPConv: Learning Local Flattening for Point Convolution
We introduce FPConv, a novel surface-style convolution operator designed for 3D point cloud analysis.
Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image
Given a single depth image, our method first goes through the 3D volume branch to obtain a volumetric scene reconstruction as a guide to the next view inpainting step, which attempts to make up the missing information; the third step involves projecting the volume under the same view of the input, concatenating them to complete the current view depth, and integrating all depth into the point cloud.
CaricatureShop: Personalized and Photorealistic Caricature Sketching
To construct the mapping between 2D sketches and a vertex-wise scaling field, a novel deep learning architecture is developed.
