Nathan Jacobs

Nathan Jacobs earned a Ph.D. in Computer Science at Washington University in St. Louis (2010). After many years at the University of Kentucky, he is currently a Professor in the Computer Science & Engineering department at Washington University in St. Louis. Dr. Jacobs' research area is computer vision; his specialty is developing learning-based algorithms and systems for processing large-scale image collections. His current focus is on developing techniques for mining information about people and the natural world from geotagged imagery, including images from social networks, publicly available outdoor webcams, and satellites. His research has been funded by NSF, NIH, DARPA, IARPA, NGA, ARL, AFRL, and Google.

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current roles

• Professor @ WashU: Computer Science & Engineering (primary), Electrical & Systems Engineering, Computational and Data Science, and Imaging Science
• Director: Multimodal Vision Research Laboratory
• Assistant Vice Provost for Digital Transformation
• Co-Director: WashU Geospatial Research Initiative
• Research Council Member: Taylor Geospatial Institute

selected recent publications

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

   close  

   @inproceedings{qiao2025genstereo,
     annotation = {spotlight,generative,geometric},
     author = {Qiao, Feng and Xiong, Zhexiao and Xing, Eric and Jacobs, Nathan},
     pdf = {https://arxiv.org/pdf/2503.12720},
     title = {Towards Open-World Generation of Stereo Images and Unsupervised Matching},
     booktitle = {IEEE International Conference on Computer Vision (ICCV)},
     project = {https://qjizhi.github.io/genstereo/},
     code = {https://github.com/Qjizhi/GenStereo},
     linkedin = {https://www.linkedin.com/posts/jacobsn_new-paper-alert-genstereo-towards-activity-7311027987846438913-5DTA?utm_source=share&utm_medium=member_desktop&rcm=ACoAAACWgMUBbrOLvty2wxK6klz29_SYYIMtEis},
     year = {2025},
     day = {20},
     month = oct,
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
     eprint = {2503.12720}
   }
   

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

   close  

   @inproceedings{sastry2025entailment,
     annotation = {remote_sensing,spotlight,conservation},
     author = {Sastry, Srikumar and Dhakal, Aayush and Xing, Eric and Khanal, Subash and Jacobs, Nathan},
     booktitle = {IEEE International Conference on Computer Vision (ICCV)},
     project = {https://vishu26.github.io/RCME/index.html},
     title = {Global and Local Entailment Learning for Natural World Imagery},
     pdf = {https://arxiv.org/pdf/2506.21476},
     volume = {2506.21476},
     year = {2025},
     day = {20},
     month = oct,
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
     eprint = {2506.21476}
   }
   

3. 

   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

   close  

   @inproceedings{xing2025cir,
     annotation = {spotlight,vlm},
     author = {Xing, Eric and Kolouju, Pranavi and Pless, Robert and Stylianou, Abby and Jacobs, Nathan},
     booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
     title = {{ConText-CIR}: Learning from Concepts in Text for Composed Image Retrieval},
     thumbnail = {/thumbnails/context-cir.jpg},
     pdf = {https://arxiv.org/pdf/2505.20764},
     linkedin = {https://www.linkedin.com/posts/jacobsn_if-you-are-at-cvpr-please-stop-by-our-poster-activity-7339745971360145411-eHCk?utm_source=share&utm_medium=member_desktop&rcm=ACoAAACWgMUBbrOLvty2wxK6klz29_SYYIMtEis},
     code = {https://github.com/mvrl/ConText-CIR},
     month = jun,
     day = {12},
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
     eprint = {2505.20764},
     year = {2025}
   }
   

4. 

   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

   close  

   @inproceedings{dhakal2025range,
     annotation = {spotlight,remote_sensing,conservation},
     author = {Dhakal, Aayush and Sastry, Srikumar and Khanal, Subash and Ahmad, Adeel and Xing, Eric and Jacobs, Nathan},
     booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
     thumbnail = {/thumbnails/range.jpg},
     pdf = {https://arxiv.org/pdf/2502.19781},
     linkedin = {https://www.linkedin.com/posts/jacobsn_range-retrieval-augmented-neural-fields-activity-7301277448279638016-q_vx?utm_source=share&utm_medium=member_desktop&rcm=ACoAAACWgMUBbrOLvty2wxK6klz29_SYYIMtEis},
     title = {{RANGE}: Retrieval Augmented Neural Fields for Multi-Resolution Geo-Embeddings},
     month = jun,
     day = {12},
     year = {2025},
     code = {https://github.com/mvrl/RANGE},
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
     eprint = {2502.19781}
   }
   

5. 

   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

   close  

   @article{xiong2025mvps,
     annotation = {remote_sensing,spotlight},
     title = {Mixed-View Panorama Synthesis using Geospatially Guided Diffusion},
     author = {Xiong, Zhexiao and Xing, Xin and Workman, Scott and Khanal, Subash and Jacobs, Nathan},
     journal = {Transactions on Machine Learning Research (TMLR)},
     year = {2025},
     eprint = {2407.09672},
     thumbnail = {/thumbnails/mixedview.jpg},
     linkedin = {https://www.linkedin.com/posts/jacobsn_new-paper-alert-mixed-view-panorama-synthesis-activity-7340423839358570496-Wr8_?utm_source=share&utm_medium=member_desktop&rcm=ACoAAACWgMUBbrOLvty2wxK6klz29_SYYIMtEis},
     month = may,
     archiveprefix = {arXiv},
     author+an = {5=highlight},
     project = {https://mixed-view.github.io/},
     pdf = {https://arxiv.org/pdf/2407.09672},
     primaryclass = {cs.CV}
   }
   

6. 

   Sastry S, Khanal S, Dhakal A, Ahmad A, Jacobs N. 2025. TaxaBind: A Unified Embedding Space for Ecological Applications. In: IEEE Winter Conference on Applications of Computer Vision (WACV).
   bibtex | paper | website | linkedin | code

   close  

   @inproceedings{sastry2025taxa,
     annotation = {remote_sensing,spotlight,conservation},
     title = {{TaxaBind}: A Unified Embedding Space for Ecological Applications},
     author = {Sastry, Srikumar and Khanal, Subash and Dhakal, Aayush and Ahmad, Adeel and Jacobs, Nathan},
     year = {2025},
     month = feb,
     booktitle = {IEEE Winter Conference on Applications of Computer Vision (WACV)},
     author+an = {5=highlight},
     archiveprefix = {arXiv},
     thumbnail = {/thumbnails/taxabind.jpg},
     primaryclass = {cs.CV},
     eprint = {2411.00683},
     code = {https://github.com/mvrl/TaxaBind},
     project = {https://vishu26.github.io/taxabind},
     linkedin = {https://www.linkedin.com/posts/jacobsn_im-excited-to-share-that-taxabind-a-unified-activity-7259230411728277504-HgXc?utm_source=share&utm_medium=member_desktop&rcm=ACoAAACWgMUBbrOLvty2wxK6klz29_SYYIMtEis},
     pdf = {https://openaccess.thecvf.com/content/WACV2025/papers/Sastry_TaxaBind_A_Unified_Embedding_Space_for_Ecological_Applications_WACV_2025_paper.pdf}
   }
   

7. 

   Kerner H, Chaudhari S, Ghosh A, Robinson C, Ahmad A, Choi E, Jacobs N, Holmes C, Mohr M, Dodhia R, Ferres JML, Marcus J. 2025. Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation. In: Association for the Advancement of Artificial Intelligence (AAAI).
   bibtex | paper | website | linkedin

   close  

   @inproceedings{kerner2025ftw,
     annotation = {spotlight,remote_sensing,agriculture},
     linkedin = {https://www.linkedin.com/posts/adeel-ahmad-gis_fields-of-the-world-a-comprehensive-benchmark-activity-7246891284445958144-9Qe5?utm_source=share&utm_medium=member_desktop&rcm=ACoAAACWgMUBbrOLvty2wxK6klz29_SYYIMtEis},
     title = {{Fields of The World}: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation},
     author = {Kerner, Hannah and Chaudhari, Snehal and Ghosh, Aninda and Robinson, Caleb and Ahmad, Adeel and Choi, Eddie and Jacobs, Nathan and Holmes, Chris and Mohr, Matthias and Dodhia, Rahul and Ferres, Juan M. Lavista and Marcus, Jennifer},
     author+an = {7=highlight},
     thumbnail = {/thumbnails/ftw.jpg},
     booktitle = {Association for the Advancement of Artificial Intelligence (AAAI)},
     volume = {2409.16252},
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
     eprint = {2409.16252},
     pdf = {https://arxiv.org/pdf/2409.16252},
     day = {27},
     month = feb,
     year = {2025},
     project = {https://fieldsofthe.world/}
   }
   

8. 

   Sarkar A, Sastry S, Pirinen A, Zhang C, Jacobs N, Vorobeychik Y. 2024. GOMAA-Geo: GOal Modality Agnostic Active Geo-localization. In: Neural Information Processing Systems (NeurIPS).
   bibtex | paper | linkedin | code

   close  

   @inproceedings{sarkar2024gomaageo,
     annotation = {spotlight,remote_sensing,localization},
     title = {{GOMAA-Geo}: GOal Modality Agnostic Active Geo-localization},
     author = {Sarkar, Anindya and Sastry, Srikumar and Pirinen, Aleksis and Zhang, Chongjie and Jacobs, Nathan and Vorobeychik, Yevgeniy},
     year = {2024},
     month = dec,
     day = {9},
     booktitle = {Neural Information Processing Systems (NeurIPS)},
     eprint = {2406.01917},
     archiveprefix = {arXiv},
     thumbnail = {/thumbnails/gomaa.jpg},
     author+an = {5=highlight},
     pdf = {https://papers.nips.cc/paper_files/paper/2024/file/bd8b52c2fefdb37e3b3953a37408e9dc-Paper-Conference.pdf},
     arxiv = {https://arxiv.org/pdf/2406.01917},
     code = {https://github.com/mvrl/GOMAA-Geo},
     linkedin = {https://www.linkedin.com/posts/jacobsn_im-excited-to-announce-that-gomaa-geo-activity-7244782724610211840-43Vs?utm_source=share&utm_medium=member_desktop},
     primaryclass = {cs.CV}
   }
   

9. 

   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. DOI: 10.1145/3664647.3681620.
   bibtex | paper | doi | linkedin

   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},
     linkedin = {https://www.linkedin.com/posts/jacobsn_im-excited-to-announce-our-paper-psm-learning-activity-7256664586563563520-w6pq?utm_source=share&utm_medium=member_desktop},
     author+an = {7=highlight},
     pdf = {https://arxiv.org/pdf/2408.07050},
     doi = {10.1145/3664647.3681620},
     eprint = {2408.07050},
     archiveprefix = {arXiv},
     primaryclass = {cs.CV},
     month = oct,
     day = {28},
     year = {2024}
   }
   

10. 

    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 | linkedin

    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},
      linkedin = {https://www.linkedin.com/posts/jacobsn_im-excited-to-introduce-frossl-frobenius-activity-7242907962275459073-Kqop?utm_source=share&utm_medium=member_desktop},
      archiveprefix = {arXiv},
      primaryclass = {cs.LG}
    }