16 citations · 35 across the 19 of their papers we have counts for
11 papers · 1 filter
VDEGaussian: Video Diffusion Enhanced 4D Gaussian Splatting for Dynamic Urban Scenes Modeling
Yuru Xiao, Zihan Lin, Chao Lu +7
Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gaussian Splatting have achieved fine…
MCGS: Multiview Consistency Enhancement for Sparse-View 3D Gaussian Radiance Fields
Yuru Xiao, Deming Zhai, Wenbo Zhao +3
Radiance fields represented by 3D Gaussians excel at synthesizing novel views, offering both high training efficiency and fast rendering. However, with sparse input views, the lack…
Spatial Annealing for Efficient Few-shot Neural Rendering
Yuru Xiao, Deming Zhai, Wenbo Zhao +3
Neural Radiance Fields (NeRF) with hybrid representations have shown impressive capabilities for novel view synthesis, delivering high efficiency. Nonetheless, their performance si…
Mesh Denoising Transformer
Wenbo Zhao, Xianming Liu, Deming Zhai +2
Mesh denoising, aimed at removing noise from input meshes while preserving their feature structures, is a practical yet challenging task. Despite the remarkable progress in learnin…
SGCNeRF: Few-Shot Neural Rendering via Sparse Geometric Consistency Guidance
Yuru Xiao, Xianming Liu, Deming Zhai +3
Neural Radiance Field (NeRF) technology has made significant strides in creating novel viewpoints. However, its effectiveness is hampered when working with sparsely available views…
Super-Resolving Face Image by Facial Parsing Information
Chenyang Wang, Junjun Jiang, Zhiwei Zhong +2
Face super-resolution is a technology that transforms a low-resolution face image into the corresponding high-resolution one. In this paper, we build a novel parsing map guided fac…
Learning Towards the Largest Margins
Xiong Zhou, Xianming Liu, Deming Zhai +3
One of the main challenges for feature representation in deep learning-based classification is the design of appropriate loss functions that exhibit strong discriminative power. Th…
Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon
Yiqi Zhong, Xianming Liu, Deming Zhai +2
Estimating the risk level of adversarial examples is essential for safely deploying machine learning models in the real world. One popular approach for physical-world attacks is to…
Fully Unsupervised Person Re-identification viaSelective Contrastive Learning
Bo Pang, Deming Zhai, Junjun Jiang +1
Person re-identification (ReID) aims at searching the same identity person among images captured by various cameras. Unsupervised person ReID attracts a lot of attention recently,…
Single Image Deraining via Scale-space Invariant Attention Neural Network
Bo Pang, Deming Zhai, Junjun Jiang +1
Image enhancement from degradation of rainy artifacts plays a critical role in outdoor visual computing systems. In this paper, we tackle the notion of scale that deals with visual…
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis
Ruifeng Shi, Deming Zhai, Xianming Liu +2
Plant diseases serve as one of main threats to food security and crop production. It is thus valuable to exploit recent advances of artificial intelligence to assist plant disease…