Everything You Ever Wanted To Know About Computer Vision
Here's A Look Why It's So Awesome.
最近发表
课题组最新论文被计算机视觉国内顶会 PRCV 2023 录用
课题组最新论文Anime Sketch Coloring Based on Self-Attention Gate and Progressive PatchGAN 被大会正式录用
人工智能在文化遗产保护传承中的价值研究
人工智能在文化遗产保护和传承中的应用具有巨大潜力，可以提升保护管理能力、挖掘文化价值、提高展示水平、扩大传承影响力，并提供智能化的公共文化服务。
实验室最新论文被期刊JOURNAL OF ELECTRONIC IMAGING选为封面
本实验室2023年7月最新发表的论文 《Thangka mural style transfer based on progressive style-attentional network and multi-level loss function》 被 SCI 期刊 《Journal of Electronic Imaging（JEI）》 选为封面。
Everything You Ever Wanted To Know About Computer Vision.
Here’s A Look Why It’s So Awesome.
Microsoft Researchers Present InstructDiffusion: A Unifying and Generic AI Framework for Aligning Computer Vision Tasks with Human Instructions
In a groundbreaking stride towards adaptable, generalist vision models, researchers from Microsoft Research Asia have unveiled InstructDiffusion.
置顶文章
Image Auto Line Drawing
Digital drawings blend art appreciation and preservation via edge detection.
Image Intelligent Inpainting
AI inpainting restores damaged art, filling missing parts for image restoration.
Image Sketch Coloring
AI sketch auto-coloring gains attention in computer vision, recognizing and coloring faces, clothes, and background components, enhancing image illustration.
Image Style Transfer
Style transfer: Recompose images in artistic styles, like famous paintings.
Image Super Resolution
Image Super Resolution enhances low-resolution images to high-resolution quality.
In Tibet, innovative thangka designs emerge
最近出版
- Image Inpainting of Thangka Murals Using Edge-assisted Feature Fusion and Self Attention Based Local Refine Network
- Thangka Mural Style Transfer Based on Progressive Style-Attentional Network and Multi-Level Loss Function
- Thangka Sketch Colorization Based on Multi-Level Adaptive-Instance-Normalized Color Fusion and Skip Connection Attention
- Wang N., Wang W., Hu W., Fenster A., Li S. (2020) Damage Sensitive and Original Restoration Driven Thanka Mural Inpainting. In: Peng Y. et al. (eds) Pattern Recognition and Computer Vision. PRCV 2020. Lecture Notes in Computer Science, vol 12305. Springer, Cham. Doi: 10.1007/978-3-030-60633-6_12
- N. Wang, W. Wang, W. Hu, A. Fenster and S. Li, "Thanka Mural Inpainting Based on Multi-Scale Adaptive Partial Convolution and Stroke-Like Mask," in IEEE Transactions on Image Processing, vol. 30, pp. 3720-3733, 2021, Doi: 10.1109/TIP.2021.3064268.
- N. Wang, W. Wang and W. Hu, "Thangka Mural Line Drawing Based on Cross Dense Residual Architecture and Hard Pixel Balancing," in IEEE Access, vol. 9, pp. 48841-48850, 2021, Doi: 10.1109/ACCESS.2021.3068199.
- Wang, N., Wang, W., Hu, W. (2022). Thangka Mural Line Drawing Based on Dense and Dual-Residual Architecture. In: , et al. Pattern Recognition and Computer Vision. PRCV 2022. Lecture Notes in Computer Science, vol 13534. Springer, Cham. Doi: 10.1007/978-3-031-18907-4_12
实验室介绍
The Computer Vision Lab of Northwest Minzu University focuses on artificial intelligence-based computer vision problems. Our main research includes image super-resolution, image style transfer, image auto restoration, image auto coloring, and auto line-extraction of ancient mural images. Our vision is to protect human traditional culture and discover the beauty of the traditional culture using computer science and AI technology.