Search Results for author:
Found 12 papers, 6 papers with code
Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior
In this work, we investigate the problem of creating high-fidelity 3D content from only a single image.
Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion
This paper presents a 3D generative model that uses diffusion models to automatically generate 3D digital avatars represented as neural radiance fields.
3D GAN Inversion with Facial Symmetry Prior
It is natural to associate 3D GANs with GAN inversion methods to project a real image into the generator's latent space, allowing free-view consistent synthesis and editing, referred as 3D GAN inversion.
Pretraining is All You Need for Image-to-Image Translation
We propose to use pretraining to boost general image-to-image translation.
Backward bifurcation, basic reinfection number and robustness of a SEIRE epidemic model with reinfection
That is, the system has backward bifurcation and the disease cannot be eradicated.
Bootstrap Motion Forecasting With Self-Consistent Constraints
We present a novel framework for motion forecasting with Dual Consistency Constraints and Multi-Pseudo-Target supervision.
Ranked #9 on
Motion Forecasting
on Argoverse CVPR 2020
Backward bifurcation and saddle-node bifurcation in virus-immune dynamics
The values of backward bifurcation point and saddle node bifurcation point are the elite control threshold and post-treatment control threshold respectively.
High-Fidelity GAN Inversion for Image Attribute Editing
With a low bit-rate latent code, previous works have difficulties in preserving high-fidelity details in reconstructed and edited images.
Dual-Camera Super-Resolution with Aligned Attention Modules
We present a novel approach to reference-based super-resolution (RefSR) with the focus on dual-camera super-resolution (DCSR), which utilizes reference images for high-quality and high-fidelity results.
Internal Video Inpainting by Implicit Long-range Propagation
We propose a novel framework for video inpainting by adopting an internal learning strategy.
Image Inpainting with External-internal Learning and Monochromic Bottleneck
Although recent inpainting approaches have demonstrated significant improvements with deep neural networks, they still suffer from artifacts such as blunt structures and abrupt colors when filling in the missing regions.
Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records
The goal is to facilitate the learning process in the target segments by leveraging the learned knowledge from data-sufficient source segments.
