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Interactive 3D Vision & Learning Lab (IVL)
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The Interactive 3D Vision & Learning Lab (IVL) led by Srinath Sridhar, part of Brown Visual Computing, works on 3D computer vision and machine learning problems to better understand how humans interact with the world. Our research spans 3D spatiotemporal visual understanding of objects, humans in motion, and human-object interactions. Please see the publications tab for details on our research.

Prospective Students/Postdocs: We are always looking for motivated students/postdocs to join us. Please see the Openings page for more details.

Updates

More Updates

  • Feb-2023 IVL will present papers on canonicalizing neural fields, room rearrangement, and text-to-3D shape at CVPR 2023. More details coming soon.

  • Oct-2022 At NeurIPS, Rao Fu will be presenting our work on recursive 3D shape generation. Please see the project page for details.

  • Jun-2022 At CVPR, we will be presenting a paper on 3D pose canonicalization (ConDor) and a tutorial on neural fields. Please see the ConDor project page and Neural Fields tutorial page for more details.

  • Apr-2022 Our Eurographics STAR report and companion website provides a consolidated overview of coordinate-based neural networks (neural fields) in visual computing and beyond by reviewing over 250 papers.

  • Mar-2022 Srinath received the NSF CAREER award that will help further the group's research on 3D perception of human physical skills.

  • Oct-2021 I helped co-organize the Second 3DReps workshop at ICCV. The workshop recording is now available at this link.

  • Oct-2021 HuMoR, a human motion model for robust pose estimation will be presented at ICCV 2021.

  • Apr-2021 Srinath received a Google Research Scholar award to further the group's research on object-centric perception/synthesis for mixed reality.

  • Mar-2021 Our upcoming ICRA paper shows how to learn to densely reconstruct and canonicalize shapes with only weak supervision. Please see the project page for details, code, and data.

  • Nov-2020 Our upcoming NeurIPS spotlight paper shows how to learn 3D canonical spatiotemporal representations of dynamically moving point clouds. Please see the project page for details.

  • Aug-2020 We organized the 3DReps Workshop at ECCV 2020. You can watch the recorded sessions on YouTube (Link: Session 1, Session 2).

  • Aug-2020 Upcoming paper at ECCV on sparse multiview 3D surface recontruction aka Pix2Surf.

  • Jan-2020 I am serving on the program committee (Area Chair) for IEEE VR 2020.

  • Jan-2020 Paper on predicting object dynamics of previously unseen objects accepted to WACV.

  • Dec-2019 Davis Rempe is presenting our paper on multi-view aggregation for 3D reconstruction at NeurIPS. Code and datasets are available.

  • Jun-2019 Watch the interview we did for our CVPR 2019 paper.

  • May-2019 Our paper on learning to generate human-object interactions was awarded an honorable mention at Eurographics 2019. Read my blog post on this work on the SAIL Blog.

  • Mar-2019 Can we estimate the 6D pose and size of novel object instances never encountered before? Our upcoming CVPR oral paper shows one way (video).

  • Mar-2019 Read my Twitter thread about interesting hand facts that you may not have known before.

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