activity
20202026
most citedConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes

1 citations · 2 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Appearance Pointers -- Multimodal Region Control of Diffusion Transformers

Rahul Sajnani, Yulia Gryaditskaya, Radomír Měch +2

Controllable image generation remains challenging for creative professionals, who often require precise regional control over materials, object identities, and spatial arrangements…

cs.CV2025

GenHSI: Controllable Generation of Human-Scene Interaction Videos

Zekun Li, Rui Zhou, Rahul Sajnani +3

Large-scale pre-trained video diffusion models have exhibited remarkable capabilities in diverse video generation. However, existing solutions face several challenges in generating…

cs.CV2024

GeoDiffuser: Geometry-Based Image Editing with Diffusion Models

Rahul Sajnani, Jeroen Vanbaar, Jie Min +2

The success of image generative models has enabled us to build methods that can edit images based on text or other user input. However, these methods are bespoke, imprecise, requir…

cs.CV2023★ 1 cited

LEGO-Net: Learning Regular Rearrangements of Objects in Rooms

Qiuhong Anna Wei, Sijie Ding, Jeong Joon Park +4

Humans universally dislike the task of cleaning up a messy room. If machines were to help us with this task, they must understand human criteria for regular arrangements, such as s…

cs.CV2022

Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields

Rohith Agaram, Shaurya Dewan, Rahul Sajnani +3

Coordinate-based implicit neural networks, or neural fields, have emerged as useful representations of shape and appearance in 3D computer vision. Despite advances, however, it rem…

cs.CV2022★ 1 cited

ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes

Rahul Sajnani, Adrien Poulenard, Jivitesh Jain +3

Progress in 3D object understanding has relied on manually canonicalized shape datasets that contain instances with consistent position and orientation (3D pose). This has made it…

cs.CV2020

DRACO: Weakly Supervised Dense Reconstruction And Canonicalization of Objects

Rahul Sajnani, AadilMehdi Sanchawala, Krishna Murthy Jatavallabhula +2

We present DRACO, a method for Dense Reconstruction And Canonicalization of Object shape from one or more RGB images. Canonical shape reconstruction, estimating 3D object shape in…

cs.RO2020

BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View

Swapnil Daga, Gokul B. Nair, Anirudha Ramesh +3

In this paper, we present BirdSLAM, a novel simultaneous localization and mapping (SLAM) system for the challenging scenario of autonomous driving platforms equipped with only a mo…

cs.RO2020

Multi-object Monocular SLAM for Dynamic Environments

Gokul B. Nair, Swapnil Daga, Rahul Sajnani +4

In this paper, we tackle the problem of multibody SLAM from a monocular camera. The term multibody, implies that we track the motion of the camera, as well as that of other dynamic…