Rahul Sajnani

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I am a Computer Science Ph.D. Candidate at Brown University advised by Srinath Sridhar. My current research interests revolves around understanding and manipulating implicit learnt representations of foundational models such as Stable Diffusion, Video Diffusion Models, CLIP, and DinoV2 to extend their capabilities for geometry editing, novel view synthesis, scene reconstruction, and motion control!

My research also delves into estimating canonical representations of objects [1,2,3] and modeling their inter-object interactions [4]. Prior to object understanding, I have also worked on visual localization of automobiles for SLAM [5] and improving mapping for autonomous driving at RRC, IIIT-Hyderabad.

I am fortunate to be advised by Leonidas Guibas, George Konidaris, Daniel Ritchie, Jeroen Vanbaar, Kapil Katyal, K. Madhava Krishna and Kavita Vemuri.

Google Scholar / Email / GitHub / X / Linkedin / ResearchGate

Featured News

Oct 28, 2024 Our work GeoDiffuser is accepted to WACV 2025 :tada:! See you in Arizona! We perform geometry-based image editing with T2I diffusion models without any training or model / fine-tuning.
Oct 24, 2024 I will present literature on Video Diffusion Models with a focus on camera/motion conditioned models at Brown IVL & BVC. See slides here.
Apr 01, 2024 I will present GeoDiffuser, a method to perform geometry-based image editing with T2I diffusion models at NYC Computer Vision Day. Our work does not need any training or model fine-tuning!
Jun 24, 2023 I will join Amazon Robotics as an Applied Scientist to improve robot perception and item identification using Generative models.
Jun 20, 2023 Check out our works Cafi-Net & Lego-Net at CVPR 2023!
Jun 01, 2022 We will be presenting ConDor, a method to perform unsupervised 3D pose canonicalization of full and partial shapes at CVPR 2022. Our work also performs automatic co-part segmentation!

Featured Publications

  1. GeoDiffuser_edit.gif
    GeoDiffuser: Geometry-Based Image Editing with Diffusion Models
    Rahul Sajnani, Jeroen Vanbaar, Jie Min, Kapil Katyal, and Srinath Sridhar
    In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025
  2. CaFi_teaser.jpg
    Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields
    Rohith Agaram, Shaurya Dewan, Rahul Sajnani, Adrien Poulenard, Madhava Krishna, and Srinath Sridhar
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2023
  3. lego-net.png
    LEGO-Net: Learning Regular Rearrangements of Objects in Rooms
    Qiuhong Anna Wei, Sijie Ding, Jeong Joon Park, Rahul Sajnani, Adrien Poulenard, Srinath Sridhar, and Leonidas Guibas
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2023
  4. ConDor.png
    ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes
    Rahul Sajnani, Adrien Poulenard, Jivitesh Jain, Radhika Dua, Leonidas J. Guibas, and Srinath Sridhar
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2022
  5. draco.png
    DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects
    Rahul Sajnani, AadilMehdi J. Sanchawala, Krishna Murthy Jatavallabhula, Srinath Sridhar, and K. Madhava Krishna
    2021 IEEE International Conference on Robotics and Automation (ICRA), Jun 2021
  6. mom-slam.png
    Multi-object Monocular SLAM for Dynamic Environments
    Gokul B. Nair, Swapnil Daga, Rahul Sajnani, Anirudh Ramesh, Junaid Ahmed Ansari, and K. Madhava Krishna
    2020 IEEE Intelligent Vehicles Symposium (IV), Jun 2020