In this paper, we propose a novel framework, Tracking-free Relightable A...
In this paper, we tackle the challenging problem of 3D keypoint estimati...
In this work, we introduce a new approach for artistic face stylization....
Personalizing generative models offers a way to guide image generation w...
Given a 3D object, kinematic motion prediction aims to identify the mobi...
We present Unified Contrastive Arbitrary Style Transfer (UCAST), a novel...
In this work, we tackle the challenging problem of learning-based single...
An accurate understanding of omnidirectional environment lighting is cru...
The artistic style within a painting is the means of expression, which
i...
Despite the impressive results of arbitrary image-guided style transfer
...
In this work, we tackle the challenging problem of arbitrary image style...
In this paper, we tackle the challenging problem of point cloud completi...
In this work, we present a new method for 3D face reconstruction from
mu...
Developing deep neural networks to generate 3D scenes is a fundamental
p...
Sampling, grouping, and aggregation are three important components in th...
This paper introduces HPNet, a novel deep-learning approach for segmenti...
Recent years have witnessed significant progress in 3D hand mesh recover...
Semi-supervised domain adaptation (SSDA) methods have demonstrated great...
Video style transfer is getting more attention in AI community for its
n...
Multimodal and multi-domain stylization are two important problems in th...
Object detection has achieved remarkable progress in the past decade.
Ho...
Visual aesthetic assessment has been an active research field for decade...
In this work, we propose a novel meta-learning approach for few-shot
cla...
Time-lapse videos usually contain visually appealing content but are oft...
We introduce a new silhouette-based representation for modeling clothed ...
We present a deep generative scene modeling technique for indoor
environ...
Real-world applications could benefit from the ability to automatically
...