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of 8
pro vyhledávání: '"Sajnani, Rahul"'
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, require additional information, or are limited to only 2D image edits. We pr
Externí odkaz:
http://arxiv.org/abs/2404.14403
Autor:
Wei, Qiuhong Anna, Ding, Sijie, Park, Jeong Joon, Sajnani, Rahul, Poulenard, Adrien, Sridhar, Srinath, Guibas, Leonidas
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 several types of symmetry, co-linearity or co-circularity, spacing unif
Externí odkaz:
http://arxiv.org/abs/2301.09629
Autor:
Agaram, Rohith, Dewan, Shaurya, Sajnani, Rahul, Poulenard, Adrien, Krishna, Madhava, Sridhar, Srinath
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 remains challenging to build neural fields for categories of objects with
Externí odkaz:
http://arxiv.org/abs/2212.02493
Autor:
Sajnani, Rahul, Poulenard, Adrien, Jain, Jivitesh, Dua, Radhika, Guibas, Leonidas J., Sridhar, Srinath
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 hard to generalize these methods to in-the-wild shapes, eg., from inte
Externí odkaz:
http://arxiv.org/abs/2201.07788
Autor:
Sajnani, Rahul, Sanchawala, AadilMehdi, Jatavallabhula, Krishna Murthy, Sridhar, Srinath, Krishna, K. Madhava
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 a coordinate space canonicalized for scale, rotation, and translation
Externí odkaz:
http://arxiv.org/abs/2011.12912
Autor:
Daga, Swapnil, Nair, Gokul B., Ramesh, Anirudha, Sajnani, Rahul, Ansari, Junaid Ahmed, Krishna, K. Madhava
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 monocular camera. BirdSLAM tackles challenges faced by other monocular S
Externí odkaz:
http://arxiv.org/abs/2011.07613
Autor:
Nair, Gokul B., Daga, Swapnil, Sajnani, Rahul, Ramesh, Anirudha, Ansari, Junaid Ahmed, Jatavallabhula, Krishna Murthy, Krishna, K. Madhava
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 participants in the scene. The quintessential challenge in dynamic sc
Externí odkaz:
http://arxiv.org/abs/2002.03528
Publikováno v:
Proceedings of the Annual Meeting of the Cognitive Science Society, vol 44, iss 44
Images are a powerful medium known to induce empathy and emotional response in people. In political protests it has the power for a people-initiated policy change and signifies the deep symbolism of a political system. In this study, we aim to quanti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______325::f1a0e6c2e704343bcab9d5440614c7ab
https://escholarship.org/uc/item/1rn4m0sh
https://escholarship.org/uc/item/1rn4m0sh