René's URL Explorer Experiment


Title: Jianwei Yang’s Homepage

Open Graph Title: Jianwei Yang’s Homepage

Open Graph Description: About me

Opengraph URL: https://jwyang.github.io/

direct link

Domain: jwyang.github.io

Hey, it has json ld scripts: 
 { "@context" : "http://schema.org", "@type" : "Person", "name" : "Jianwei Yang", "url" : "https://jwyang.github.io", "sameAs" : null }
og:localeen-US
og:site_nameJianwei Yang's Homepage
HandheldFriendlyTrue
MobileOptimized320
NoneAbout me
msapplication-TileColor#000000
msapplication-TileImagehttps://jwyang.github.io/images/mstile-144x144.png?v=M44lzPylqQ
msapplication-confighttps://jwyang.github.io/images/browserconfig.xml?v=M44lzPylqQ
theme-color#ffffff

Links:

Jianwei Yang's Homepagehttps://jwyang.github.io/
Twitterhttps://twitter.com/jw2yang4ai
Githubhttps://github.com/jwyang
Google Scholarhttps://scholar.google.com/citations?user=Cl9byD8AAAAJ&hl=en
UniCLhttps://arxiv.org/abs/2204.03610
RegionCLIPhttps://arxiv.org/abs/2112.09106
GLIPhttps://arxiv.org/abs/2112.03857
Florencehttps://arxiv.org/abs/2111.11432
X-Decoderhttps://x-decoder-vl.github.io/
SEEMhttps://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once
Semantic-SAMhttps://github.com/UX-Decoder/Semantic-SAM
LLaVahttps://github.com/haotian-liu/LLaVA
SoM Prompting for GPT-4Vhttps://som-gpt4v.github.io/
Phi-3-Visionhttps://arxiv.org/pdf/2404.14219
Project Magmahttps://microsoft.github.io/Magma/
Magmahttps://microsoft.github.io/Magma/
TraceVLAhttps://arxiv.org/pdf/2412.10345
Florence-VLhttps://arxiv.org/pdf/2412.04424
OLA-VLMhttps://arxiv.org/pdf/2412.09585
OmniParserhttps://huggingface.co/microsoft/OmniParser
codehttps://github.com/microsoft/OmniParser
LAPAhttps://arxiv.org/pdf/2410.11758
TemporalBenchhttps://arxiv.org/pdf/2410.10818
BiomedParsehttps://arxiv.org/abs/2405.12971
Nature Methodshttps://www.nature.com/nmeth/
GigaPathhttps://www.nature.com/articles/s41586-024-07441-w
Naturehttps://www.nature.com/
Phi-3-Visionhttps://arxiv.org/pdf/2404.14219
bloghttps://azure.microsoft.com/en-us/blog/new-models-added-to-the-phi-3-family-available-on-microsoft-azure/
hugging facehttps://huggingface.co/collections/microsoft/phi-3-6626e15e9585a200d2d761e3
Set-of-Mark (SoM)https://som-gpt4v.github.io/
Magma: A Foundation Model for Multimodal AI Agentshttps://github.com/microsoft/Magma
1st Workshop on Video-Language Modelshttps://video-and-language-workshop-2024.webflow.io/
Microsoft Research Forum Session 4 on Multimodalityhttps://researchforum.microsoft.com/
NeurIPS 2024https://neurips.cc/
ICLR 2025https://iclr.cc/Conferences/2025
slideshttps://datarelease.blob.core.windows.net/tutorial/vision_foundation_models_2024/Jianwei_vision_in_LMM.pdf
youtubehttps://youtu.be/bDVbs-fZGUg
CVPR 2024 Tutorial on Recent Advances in Vision Foundation Modelshttps://vlp-tutorial.github.io/
CVPR 2024 Worshop on Computer Vision for Materials Sciencehttps://sites.google.com/view/cv4ms-cvpr-2024/home
3rd Computer Vision in the Wild (CVinW) Workshop at CVPR 2024https://computer-vision-in-the-wild.github.io/cvpr-2024/
slideshttps://datarelease.blob.core.windows.net/tutorial/vision_foundation_models_2023/slides/Jianwei_CVPR2023_Tutorial.pdf
youtubehttps://youtu.be/wIcTyutOlDs
CVPR 2023 Tutorial on Recent Advances in Vision Foundation Modelshttps://vlp-tutorial.github.io/2023/index.html
2nd Computer Vision in the Wild (CVinW) Workshop at CVPR 2023https://computer-vision-in-the-wild.github.io/cvpr-2023/
ICCV 2023https://iccv2023.thecvf.com/
slideshttps://datarelease.blob.core.windows.net/tutorial/VLP-Tutorial_2022/vlp_for_v_part1.pdf
youtubehttps://youtu.be/Tq7RWYWN2M0
CVPR 2022 Tutorial on Recent Advances in Vision-and-Language Pretraininghttps://vlp-tutorial.github.io/2022/
[project]https://microsoft.github.io/Magma/
[model]https://www.arxiv.org/pdf/2502.13130
[paper]https://arxiv.org/pdf/2404.14219
[model]https://huggingface.co/microsoft/Phi-3-vision-128k-instruct
[paper]https://arxiv.org/abs/2310.11441
[code]https://github.com/microsoft/SoM
[project]https://som-gpt4v.github.io/
[paper]https://arxiv.org/pdf/2111.11432.pdf
[research code]https://github.com/microsoft/UniCL
[blog]https://www.microsoft.com/en-us/research/blog/azure-ai-milestone-new-foundation-model-florence-v1-0-pushing-vision-and-vision-language-state-of-the-art/
[paper]https://arxiv.org/pdf/2307.04767.pdf
[code]https://github.com/UX-Decoder/Semantic-SAM
[paper]https://arxiv.org/pdf/2304.06718.pdf
[code]https://github.com/UX-Decoder/Segment-Everything-Everywhere-All-At-Once
[project]https://x-decoder-vl.github.io/
[paper]https://arxiv.org/pdf/2212.11270.pdf
[code]https://github.com/microsoft/X-Decoder
[huggingface demo]https://huggingface.co/xdecoder
[project]https://x-decoder-vl.github.io/
[paper]https://arxiv.org/pdf/2212.11270.pdf
[code]https://github.com/microsoft/X-Decoder
[huggingface demo]https://huggingface.co/xdecoder
[paper]https://arxiv.org/abs/2203.11926
[code]https://github.com/microsoft/FocalNet
[blog]https://www.microsoft.com/en-us/research/group/deep-learning-group/articles/focalnets-focusing-the-eyes-with-focal-modulation/
[huggingface demo]https://huggingface.co/spaces/jw2yang/focalnet-modulators
[paper]https://arxiv.org/pdf/2204.09222.pdf
[code]https://github.com/microsoft/klite
[paper]http://openaccess.thecvf.com/content/CVPR2022/papers/Li_Grounded_Language-Image_Pre-Training_CVPR_2022_paper.pdf
[code]https://github.com/microsoft/GLIP
[huggingface demo]https://huggingface.co/spaces/haotiz/glip-zeroshot-demo
[paper]http://openaccess.thecvf.com/content/CVPR2022/papers/Zhong_RegionCLIP_Region-Based_Language-Image_Pretraining_CVPR_2022_paper.pdf
[code]https://github.com/microsoft/RegionCLIP
[huggingface demo]https://huggingface.co/spaces/CVPR/regionclip-demo
[paper]https://openaccess.thecvf.com/content/CVPR2022/papers/Yang_Unified_Contrastive_Learning_in_Image-Text-Label_Space_CVPR_2022_paper.pdf
[code]https://github.com/microsoft/UniCL
[huggingface demo]https://huggingface.co/spaces/CVPR/unicl-zero-shot-img-recog
[paper]https://arxiv.org/pdf/2106.09785.pdf
[code]https://github.com/microsoft/esvit
[paper]https://proceedings.neurips.cc/paper/2021/file/fc1a36821b02abbd2503fd949bfc9131-Paper.pdf
[code]https://github.com/microsoft/Focal-Transformer
[video]https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjzk6Wm8NHyAhVCqlsKHYepD9wQtwJ6BAgDEAM&url=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DYH319yyeoVw&usg=AOvVaw27s7EE-txctmc6_BwKnnfE
[paper]https://openaccess.thecvf.com/content/ICCV2021/papers/Yang_TACo_Token-Aware_Cascade_Contrastive_Learning_for_Video-Text_Alignment_ICCV_2021_paper.pdf
Sitemaphttps://jwyang.github.io/sitemap/
GitHubhttp://github.com/jwyang
Feedhttps://jwyang.github.io/feed.xml
Jekyllhttp://jekyllrb.com
AcademicPageshttps://github.com/academicpages/academicpages.github.io
Minimal Mistakeshttps://mademistakes.com/work/minimal-mistakes-jekyll-theme/

Viewport: width=device-width, initial-scale=1.0

URLs of crawlers that visited me.