66 citations · 140 across the 21 of their papers we have counts for
21 papers
RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completion
Zhiqiang Yan, Xiang Li, Le Hui +3
Depth completion aims to recover dense depth maps from sparse ones, where color images are often used to facilitate this task. Recent depth methods primarily focus on image guided…
AltNeRF: Learning Robust Neural Radiance Field via Alternating Depth-Pose Optimization
Kun Wang, Zhiqiang Yan, Huang Tian +4
Neural Radiance Fields (NeRF) have shown promise in generating realistic novel views from sparse scene images. However, existing NeRF approaches often encounter challenges due to t…
MPM: A Unified 2D-3D Human Pose Representation via Masked Pose Modeling
Zhenyu Zhang, Wenhao Chai, Zhongyu Jiang +4
Estimating 3D human poses only from a 2D human pose sequence is thoroughly explored in recent years. Yet, prior to this, no such work has attempted to unify 2D and 3D pose represen…
Learnable Differencing Center for Nighttime Depth Perception
Zhiqiang Yan, Yupeng Zheng, Chongyi Li +2
Depth completion is the task of recovering dense depth maps from sparse ones, usually with the help of color images. Existing image-guided methods perform well on daytime depth per…
Variable Radiance Field for Real-World Category-Specific Reconstruction from Single Image
Kun Wang, Zhiqiang Yan, Zhenyu Zhang +3
Reconstructing category-specific objects using Neural Radiance Field (NeRF) from a single image is a promising yet challenging task. Existing approaches predominantly rely on proje…
Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution
Ming Cheng, Haoyu Ma, Qiufang Ma +7
Multi-stage strategies are frequently employed in image restoration tasks. While transformer-based methods have exhibited high efficiency in single-image super-resolution tasks, th…
OPDN: Omnidirectional Position-aware Deformable Network for Omnidirectional Image Super-Resolution
Xiaopeng Sun, Weiqi Li, Zhenyu Zhang +8
360° omnidirectional images have gained research attention due to their immersive and interactive experience, particularly in AR/VR applications. However, they suffer from lower an…
Multi-pooling 3D Convolutional Neural Network for fMRI Classification of Visual Brain States
Zhen Zhang, Masaki Takeda, Makoto Iwata
Neural decoding of visual object classification via functional magnetic resonance imaging (fMRI) data is challenging and is vital to understand underlying brain mechanisms. This pa…
Graph Transformer GANs for Graph-Constrained House Generation
Hao Tang, Zhenyu Zhang, Humphrey Shi +5
We present a novel graph Transformer generative adversarial network (GTGAN) to learn effective graph node relations in an end-to-end fashion for the challenging graph-constrained h…
Two-dimensional superconductors with intrinsic p-wave pairing or nontrivial band topology
Wei Qin, Jiaqing Gao, Ping Cui +1
Over the past fifteen years, tremendous efforts have been devoted to realizing topological superconductivity in realistic materials and systems, predominately propelled by their pr…
Decentralized ADMM with Compressed and Event-Triggered Communication
Zhen Zhang, Shaofu Yang, Wenying Xu
This paper focuses on the decentralized optimization problem, where agents in a network cooperate to minimize the sum of their local objective functions by information exchange and…
ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-Experts
Zhida Feng, Zhenyu Zhang, Xintong Yu +12
Recent progress in diffusion models has revolutionized the popular technology of text-to-image generation. While existing approaches could produce photorealistic high-resolution im…
Study of exotic hadrons with machine learning
Jiahao Liu, Zhenyu Zhang, Jifeng Hu +1
We analyzed the invariant mass spectrum of near-threshold exotic states for one-channel candidates with a deep neural network. It can extract the scattering length and effective ra…
Formalism for Supporting the Development of Verifiably Safe Medical Guidelines with Statecharts
Chunhui Guo, Zhicheng Fu, Zhenyu Zhang +2
Improving the effectiveness and safety of patient care is the ultimate objective for medical cyber-physical systems. Many medical best practice guidelines exist, but most of the ex…
Proximal Policy Optimization with Mixed Distributed Training
Zhenyu Zhang, Xiangfeng Luo, Tong Liu +5
Instability and slowness are two main problems in deep reinforcement learning. Even if proximal policy optimization (PPO) is the state of the art, it still suffers from these two p…
Pattern-Affinitive Propagation across Depth, Surface Normal and Semantic Segmentation
Zhenyu Zhang, Zhen Cui, Chunyan Xu +3
In this paper, we propose a novel Pattern-Affinitive Propagation (PAP) framework to jointly predict depth, surface normal and semantic segmentation. The motivation behind it comes…
A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks
Long Zhang, Xuechao Sun, Yong Li +1
Deep neural networks (DNNs) have been widely used in the fields such as natural language processing, computer vision and image recognition. But several studies have been shown that…
Model and Integrate Medical Resource Availability into Verifiably Correct Executable Medical Guidelines - Technical Report
Chunhui Guo, Zhicheng Fu, Zhenyu Zhang +2
Improving effectiveness and safety of patient care is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate can be reduced by…
Model and Integrate Medical Resource Available Times and Relationships in Verifiably Correct Executable Medical Best Practice Guideline Models (Extended Version)
Chunhui Guo, Zhicheng Fu, Zhenyu Zhang +2
Improving patient care safety is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate is significantly reduced by computeriz…
Design Verifiably Correct Model Patterns to Facilitate Modeling Medical Best Practice Guidelines with Statecharts (Technical Report)
Chunhui Guo, Zhicheng Fu, Zhenyu Zhang +2
Improving patient care safety is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate can be significantly reduced by comput…
The extremely red L dwarf ULAS J222711004547 - dominated by dust
F. Marocco, A. C. Day-Jones, P. W. Lucas +8
We report the discovery of a peculiar L dwarf from the UKIDSS LAS, ULAS J222711-004547. The very red infrared photometry (MKO J-K = 2.790.06, WISE W1-W2 = 0.650.05) of UL…