Multimodal Vision Research Laboratory

MVRL

about us

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

• 15 Jul 2024 : one paper accepted to ACM Multimedia, congrats to Subash Khanal, Eric Xing, Srikumar Sastry, Aayush Dhakal, Zhexiao Xiong, and Adeel Ahmad!
• 02 Jul 2024 : one paper accepted to PLOS ONE, congrats to Alex Levering!
• 02 Jul 2024 : one paper accepted to ECCV, congrats to Oscar Skean, Aayush Dhakal, and Luis Sanchez Giraldo!
• 22 Apr 2024 : Best Paper Award in the EARTHVISION workshop for Sat2Cap: Mapping Fine-Grained Textual Descriptions from Satellite Images
• 05 Apr 2024 : three papers accepted to CVPR workshops!
• 15 Mar 2024 : two papers accepted to IGARSS. Congrats to Aayush Dhakal, Srikumar Sastry, Subash Khanal, and Adeel Ahmad!

Check the archives for old news.

selected recent publications

See our publications page for a complete listing.

1. 

   Skean O, Dhakal A, Jacobs N, Giraldo LGS. 2024. FroSSL: Frobenius Norm Minimization for Self-Supervised Learning. In: European Conference on Computer Vision (ECCV).
   bibtex | paper

   close  

   @inproceedings{skean2024frossl,
     annotation = {spotlight},
     thumbnail = {/thumbnails/frossl.jpg},
     title = {{FroSSL}: Frobenius Norm Minimization for Self-Supervised Learning},
     author = {Skean, Oscar and Dhakal, Aayush and Jacobs, Nathan and Giraldo, Luis Gonzalo Sanchez},
     booktitle = {European Conference on Computer Vision (ECCV)},
     year = {2024},
     eprint = {2310.02903},
     pdf = {https://arxiv.org/pdf/2310.02903.pdf},
     month = oct,
     day = {1},
     author+an = {3=highlight},
     archiveprefix = {arXiv},
     primaryclass = {cs.LG}
   }
   

2. 

   Khanal S, Xing E, Sastry S, Dhakal A, Xiong Z, Ahmad A, Jacobs N. 2024. PSM: Learning Probabilistic Embeddings for Multi-scale Zero-shot Soundscape Mapping. In: ACM Multimedia.
   bibtex | paper

   close  

   @inproceedings{khanal2024psm,
     annotation = {remote_sensing,spotlight},
     author = {Khanal, Subash and Xing, Eric and Sastry, Srikumar and Dhakal, Aayush and Xiong, Zhexiao and Ahmad, Adeel and Jacobs, Nathan},
     thumbnail = {/thumbnails/psm.jpg},
     booktitle = {ACM Multimedia},
     title = {{PSM}: Learning Probabilistic Embeddings for Multi-scale Zero-shot Soundscape Mapping},
     author+an = {7=highlight},
     pdf = {https://arxiv.org/pdf/2408.07050},
     eprint = {2408.07050},
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
     month = oct,
     day = {28},
     year = {2024}
   }
   

3. 

   Sastry S, Khanal S, Dhakal A, Huang D, Jacobs N. 2024. BirdSat: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping. In: IEEE Winter Conference on Applications of Computer Vision (WACV).
   bibtex | paper | press release | linkedin | code

   close  

   @inproceedings{sastry2024bird,
     title = {{BirdSat}: Cross-View Contrastive Masked Autoencoders for Bird Species Classification and Mapping},
     author = {Sastry, Srikumar and Khanal, Subash and Dhakal, Aayush and Huang, Di and Jacobs, Nathan},
     code = {https://github.com/mvrl/BirdSAT},
     thumbnail = {/thumbnails/birdsat.jpg},
     linkedin = {https://www.linkedin.com/feed/update/urn:li:activity:7125481632219754496/},
     press = {https://engineering.wustl.edu/news/2024/For-the-birds.html},
     year = {2024},
     month = jan,
     pdf = {http://arxiv.org/pdf/2310.19168.pdf},
     booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},
     author+an = {5=highlight},
     annotation = {remote_sensing,spotlight}
   }
   

4. 

   Greenwell C, Leotta M, Crall J, Jacobs N, Purri M, Dana K, Hadzic A, Workman S. 2024. WATCH: Wide-Area Terrestrial Change Hypercube. In: IEEE Winter Conference on Applications of Computer Vision (WACV).
   bibtex | paper | code

   close  

   @inproceedings{greenwell2024watch,
     title = {WATCH: Wide-Area Terrestrial Change Hypercube},
     author = {Greenwell, Connor and Leotta, Matt and Crall, Jonathan and Jacobs, Nathan and Purri, Matthew and Dana, Kristin and Hadzic, Armin and Workman, Scott},
     year = {2024},
     thumbnail = {/thumbnails/watch.jpg},
     month = jan,
     booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},
     author+an = {4=highlight},
     code = {https://gitlab.kitware.com/computer-vision/geowatch},
     pdf = {https://openaccess.thecvf.com/content/WACV2024/papers/Greenwell_WATCH_Wide-Area_Terrestrial_Change_Hypercube_WACV_2024_paper.pdf},
     annotation = {remote_sensing,spotlight}
   }
   

5. 

   Sarkar A, Jacobs N, Vorobeychik Y. 2023. A Partially-Supervised Reinforcement Learning Framework for Visual Active Search. In: Neural Information Processing Systems (NeurIPS).
   bibtex | paper | press release | code

   close  

   @inproceedings{sarkar2023psrlvas,
     title = {A Partially-Supervised Reinforcement Learning Framework for Visual Active Search},
     author = {Sarkar, Anindya and Jacobs, Nathan and Vorobeychik, Yevgeniy},
     thumbnail = {/thumbnails/pvas.jpg},
     year = {2023},
     month = dec,
     booktitle = {Neural Information Processing Systems (NeurIPS)},
     press = {https://engineering.wustl.edu/news/2023/Meta-learning-to-find-every-needle-in-a-haystack.html},
     author+an = {2=highlight},
     pdf = {https://arxiv.org/pdf/2310.09689.pdf},
     code = {https://github.com/anindyasarkarIITH/VAS},
     annotation = {remote_sensing,spotlight}
   }
   

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