48 citations · 84 across the 12 of their papers we have counts for
13 papers
MSF-Net: Multi-Stage Feature Extraction and Fusion for Robust Photometric Stereo
Shiyu Qin, Zhihao Cai, Kaixuan Wang +2
Photometric stereo is a technique aimed at determining surface normals through the utilization of shading cues derived from images taken under different lighting conditions. Howeve…
Dense Geometry Supervision for Underwater Depth Estimation
Wenxiang Gua, Lin Qia
The field of monocular depth estimation is continually evolving with the advent of numerous innovative models and extensions. However, research on monocular depth estimation method…
Image Gradient-Aided Photometric Stereo Network
Kaixuan Wang, Lin Qi, Shiyu Qin +4
Photometric stereo (PS) endeavors to ascertain surface normals using shading clues from photometric images under various illuminations. Recent deep learning-based PS methods often…
Superpixel Cost Volume Excitation for Stereo Matching
Shanglong Liu, Lin Qi, Junyu Dong +2
In this work, we concentrate on exciting the intrinsic local consistency of stereo matching through the incorporation of superpixel soft constraints, with the objective of mitigati…
RMAFF-PSN: A Residual Multi-Scale Attention Feature Fusion Photometric Stereo Network
Kai Luo, Yakun Ju, Lin Qi +2
Predicting accurate normal maps of objects from two-dimensional images in regions of complex structure and spatial material variations is challenging using photometric stereo metho…
CLIP-Hand3D: Exploiting 3D Hand Pose Estimation via Context-Aware Prompting
Shaoxiang Guo, Qing Cai, Lin Qi +1
Contrastive Language-Image Pre-training (CLIP) starts to emerge in many computer vision tasks and has achieved promising performance. However, it remains underexplored whether CLIP…
SAWU-Net: Spatial Attention Weighted Unmixing Network for Hyperspectral Images
Lin Qi, Xuewen Qin, Feng Gao +2
Hyperspectral unmixing is a critical yet challenging task in hyperspectral image interpretation. Recently, great efforts have been made to solve the hyperspectral unmixing task via…
SSCU-Net: Spatial-Spectral Collaborative Unmixing Network for Hyperspectral Images
Lin Qi, Feng Gao, Junyu Dong +2
Linear spectral unmixing is an essential technique in hyperspectral image processing and interpretation. In recent years, deep learning-based approaches have shown great promise in…
Wallpaper Texture Generation and Style Transfer Based on Multi-label Semantics
Ying Gao, Xiaohan Feng, Tiange Zhang +4
Textures contain a wealth of image information and are widely used in various fields such as computer graphics and computer vision. With the development of machine learning, the te…
Associated Spatio-Temporal Capsule Network for Gait Recognition
Aite Zhao, Junyu Dong, Jianbo Li +2
It is a challenging task to identify a person based on her/his gait patterns. State-of-the-art approaches rely on the analysis of temporal or spatial characteristics of gait, and g…
Combining SLAM with muti-spectral photometric stereo for real-time dense 3D reconstruction
Yuanhong Xu, Pei Dong, Junyu Dong +1
Obtaining dense 3D reconstrution with low computational cost is one of the important goals in the field of SLAM. In this paper we propose a dense 3D reconstruction framework from m…
Dense 3D Facial Reconstruction from a Single Depth Image in Unconstrained Environment
Shu Zhang, Hui Yu, Ting Wang +2
With the increasing demands of applications in virtual reality such as 3D films, virtual Human-Machine Interactions and virtual agents, the analysis of 3D human face analysis is co…
A Procedural Texture Generation Framework Based on Semantic Descriptions
Junyu Dong, Lina Wang, Jun Liu +1
Procedural textures are normally generated from mathematical models with parameters carefully selected by experienced users. However, for naive users, the intuitive way to obtain a…