307 citations · 360 across the 12 of their papers we have counts for
12 papers
SealD-NeRF: Interactive Pixel-Level Editing for Dynamic Scenes by Neural Radiance Fields
Zhentao Huang, Yukun Shi, Neil Bruce +1
The widespread adoption of implicit neural representations, especially Neural Radiance Fields (NeRF), highlights a growing need for editing capabilities in implicit 3D models, esse…
Visibility-Aware Pixelwise View Selection for Multi-View Stereo Matching
Zhentao Huang, Yukun Shi, Minglun Gong
The performance of PatchMatch-based multi-view stereo algorithms depends heavily on the source views selected for computing matching costs. Instead of modeling the visibility of di…
Human Pose and Shape Estimation from Single Polarization Images
Shihao Zou, Xinxin Zuo, Sen Wang +3
This paper focuses on a new problem of estimating human pose and shape from single polarization images. Polarization camera is known to be able to capture the polarization of refle…
SparseFusion: Dynamic Human Avatar Modeling from Sparse RGBD Images
Xinxin Zuo, Sen Wang, Jiangbin Zheng +4
In this paper, we propose a novel approach to reconstruct 3D human body shapes based on a sparse set of RGBD frames using a single RGBD camera. We specifically focus on the realist…
Interlayer and Intralayer Scale Aggregation for Scale-invariant Crowd Counting
Mingjie Wang, Hao Cai, Jun Zhou +1
Crowd counting is an important vision task, which faces challenges on continuous scale variation within a given scene and huge density shift both within and across images. These ch…
ETNet: Error Transition Network for Arbitrary Style Transfer
Chunjin Song, Zhijie Wu, Yang Zhou +2
Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the seminal work of Gatys et al. However, existing state-of-the-art approaches often generat…
EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer
Zhijie Wu, Chunjin Song, Yang Zhou +2
Style transfer has been an important topic both in computer vision and graphics. Since the seminal work of Gatys et al. first demonstrates the power of stylization through optimiza…
Multi-scale Convolution Aggregation and Stochastic Feature Reuse for DenseNets
Mingjie Wang, Jun Zhou, Wendong Mao +1
Recently, Convolution Neural Networks (CNNs) obtained huge success in numerous vision tasks. In particular, DenseNets have demonstrated that feature reuse via dense skip connection…
Semi-dense Stereo Matching using Dual CNNs
Wendong Mao, Mingjie Wang, Jun Zhou +1
A robust solution for semi-dense stereo matching is presented. It utilizes two CNN models for computing stereo matching cost and performing confidence-based filtering, respectively…
Full 3D Reconstruction of Transparent Objects
Bojian Wu, Yang Zhou, Yiming Qian +2
Numerous techniques have been proposed for reconstructing 3D models for opaque objects in past decades. However, none of them can be directly applied to transparent objects. This p…
BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis
Zili Yi, Zhiqin Chen, Hao Cai +3
We introduce BSD-GAN, a novel multi-branch and scale-disentangled training method which enables unconditional Generative Adversarial Networks (GANs) to learn image representations…
DualGAN: Unsupervised Dual Learning for Image-to-Image Translation
Zili Yi, Hao Zhang, Ping Tan +1
Conditional Generative Adversarial Networks (GANs) for cross-domain image-to-image translation have made much progress recently. Depending on the task complexity, thousands to mill…