79 citations · 436 across the 36 of their papers we have counts for
14 papers · 1 filter
One-shot Talking Face Generation from Single-speaker Audio-Visual Correlation Learning
Suzhen Wang, Lincheng Li, Yu Ding +1
Audio-driven one-shot talking face generation methods are usually trained on video resources of various persons. However, their created videos often suffer unnatural mouth shapes a…
RGB-D Saliency Detection via Cascaded Mutual Information Minimization
Jing Zhang, Deng-Ping Fan, Yuchao Dai +4
Existing RGB-D saliency detection models do not explicitly encourage RGB and depth to achieve effective multi-modal learning. In this paper, we introduce a novel multi-stage cascad…
PR-RRN: Pairwise-Regularized Residual-Recursive Networks for Non-rigid Structure-from-Motion
Haitian Zeng, Yuchao Dai, Xin Yu +2
We propose PR-RRN, a novel neural-network based method for Non-rigid Structure-from-Motion (NRSfM). PR-RRN consists of Residual-Recursive Networks (RRN) and two extra regularizatio…
VidFace: A Full-Transformer Solver for Video FaceHallucination with Unaligned Tiny Snapshots
Yuan Gan, Yawei Luo, Xin Yu +2
In this paper, we investigate the task of hallucinating an authentic high-resolution (HR) human face from multiple low-resolution (LR) video snapshots. We propose a pure transforme…
VTNet: Visual Transformer Network for Object Goal Navigation
Heming Du, Xin Yu, Liang Zheng
Object goal navigation aims to steer an agent towards a target object based on observations of the agent. It is of pivotal importance to design effective visual representations of…
Write-a-speaker: Text-based Emotional and Rhythmic Talking-head Generation
Lincheng Li, Suzhen Wang, Zhimeng Zhang +4
In this paper, we propose a novel text-based talking-head video generation framework that synthesizes high-fidelity facial expressions and head motions in accordance with contextua…
Blind Motion Deblurring Super-Resolution: When Dynamic Spatio-Temporal Learning Meets Static Image Understanding
Wenjia Niu, Kaihao Zhang, Wenhan Luo +1
Single-image super-resolution (SR) and multi-frame SR are two ways to super resolve low-resolution images. Single-Image SR generally handles each image independently, but ignores t…
DSC-PoseNet: Learning 6DoF Object Pose Estimation via Dual-scale Consistency
Zongxin Yang, Xin Yu, Yi Yang
Compared to 2D object bounding-box labeling, it is very difficult for humans to annotate 3D object poses, especially when depth images of scenes are unavailable. This paper investi…
Self-Supervised Visibility Learning for Novel View Synthesis
Yujiao Shi, Hongdong Li, Xin Yu
We address the problem of novel view synthesis (NVS) from a few sparse source view images. Conventional image-based rendering methods estimate scene geometry and synthesize novel v…
ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring
Dongxu Li, Chenchen Xu, Kaihao Zhang +5
Video deblurring models exploit consecutive frames to remove blurs from camera shakes and object motions. In order to utilize neighboring sharp patches, typical methods rely mainly…
Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar
Peike Li, Xin Yu, Yi Yang
Conventional face super-resolution methods usually assume testing low-resolution (LR) images lie in the same domain as the training ones. Due to different lighting conditions and i…
Geometry-Guided Street-View Panorama Synthesis from Satellite Imagery
Yujiao Shi, Dylan Campbell, Xin Yu +1
This paper presents a new approach for synthesizing a novel street-view panorama given an overhead satellite image. Taking a small satellite image patch as input, our method genera…
Modeling the Probabilistic Distribution of Unlabeled Data forOne-shot Medical Image Segmentation
Yuhang Ding, Xin Yu, Yi Yang
Existing image segmentation networks mainly leverage large-scale labeled datasets to attain high accuracy. However, labeling medical images is very expensive since it requires soph…
Iterative Optimisation with an Innovation CNN for Pose Refinement
Gerard Kennedy, Zheyu Zhuang, Xin Yu +1
Object pose estimation from a single RGB image is a challenging problem due to variable lighting conditions and viewpoint changes. The most accurate pose estimation networks implem…