Multimodal Vision Research Laboratory

MVRL

about us

a group photo from a lab picnic

The Multimodal Vision Research Laboratory (MVRL) develops novel algorithms for image understanding and works to solve challenging problems in areas including remote sensing, image localization, and medical imaging. If you are interested in joining us, please check out our openings page for more information and a description of current open positions.

recent news

Check the archives for old news.

selected recent publications

See our publications page for a complete listing.
  1. Qiao F, Xiong Z, Xing E, Jacobs N. 2025. Towards Open-World Generation of Stereo Images and Unsupervised Matching. In: IEEE International Conference on Computer Vision (ICCV).
    bibtex | paper | website | linkedin | code
  2. Sastry S, Dhakal A, Xing E, Khanal S, Jacobs N. 2025. Global and Local Entailment Learning for Natural World Imagery. In: IEEE International Conference on Computer Vision (ICCV).
    bibtex | paper | website
  3. a thumbnail for ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval
    Xing E, Kolouju P, Pless R, Stylianou A, Jacobs N. 2025. ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
    bibtex | paper | linkedin | code
  4. a thumbnail for RANGE: Retrieval Augmented Neural Fields for Multi-Resolution Geo-Embeddings
    Dhakal A, Sastry S, Khanal S, Ahmad A, Xing E, Jacobs N. 2025. RANGE: Retrieval Augmented Neural Fields for Multi-Resolution Geo-Embeddings. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
    bibtex | paper | linkedin | code
  5. a thumbnail for Mixed-View Panorama Synthesis using Geospatially Guided Diffusion
    Xiong Z, Xing X, Workman S, Khanal S, Jacobs N. 2025. Mixed-View Panorama Synthesis using Geospatially Guided Diffusion. Transactions on Machine Learning Research (TMLR).
    bibtex | paper | website | linkedin