Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Sridhar, Srinath"'
Autor:
Dey, Arnab, Lu, Cheng-You, Comport, Andrew I., Sridhar, Srinath, Lin, Chin-Teng, Martinet, Jean
Recent advancements in radiance field rendering show promising results in 3D scene representation, where Gaussian splatting-based techniques emerge as state-of-the-art due to their quality and efficiency. Gaussian splatting is widely used for various
Externí odkaz:
http://arxiv.org/abs/2411.03086
Autor:
Karim, Md Faizal, Bollimuntha, Shreya, Hashmi, Mohammed Saad, Das, Autrio, Singh, Gaurav, Sridhar, Srinath, Singh, Arun Kumar, Govindan, Nagamanikandan, Krishna, K Madhava
Dual-arm manipulation is an area of growing interest in the robotics community. Enabling robots to perform tasks that require the coordinated use of two arms, is essential for complex manipulation tasks such as handling large objects, assembling comp
Externí odkaz:
http://arxiv.org/abs/2410.19712
Autor:
Harithas, Sudarshan, Sridhar, Srinath
This paper introduces MotionGlot, a model that can generate motion across multiple embodiments with different action dimensions, such as quadruped robots and human bodies. By leveraging the well-established training procedures commonly used in large
Externí odkaz:
http://arxiv.org/abs/2410.16623
We propose a zero-shot text-driven 3D shape deformation system that deforms an input 3D mesh of a manufactured object to fit an input text description. To do this, our system optimizes the parameters of a deformation model to maximize an objective fu
Externí odkaz:
http://arxiv.org/abs/2410.15199
Autor:
Rai, Aashish, Sridhar, Srinath
We introduce EgoSonics, a method to generate semantically meaningful and synchronized audio tracks conditioned on silent egocentric videos. Generating audio for silent egocentric videos could open new applications in virtual reality, assistive techno
Externí odkaz:
http://arxiv.org/abs/2407.20592
Autor:
Min, Chaerin, Sridhar, Srinath
Grasping is an important human activity that has long been studied in robotics, computer vision, and cognitive science. Most existing works study grasping from the perspective of synthesizing hand poses conditioned on 3D or 2D object representations.
Externí odkaz:
http://arxiv.org/abs/2406.05059
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:
Dey, Arnab, Yang, Di, Agaram, Rohith, Dantcheva, Antitza, Comport, Andrew I., Sridhar, Srinath, Martinet, Jean
Recent advances in Neural Radiance Fields (NeRF) have demonstrated promising results in 3D scene representations, including 3D human representations. However, these representations often lack crucial information on the underlying human pose and struc
Externí odkaz:
http://arxiv.org/abs/2404.06246
Autor:
Singh, Gaurav, Kalwar, Sanket, Karim, Md Faizal, Sen, Bipasha, Govindan, Nagamanikandan, Sridhar, Srinath, Krishna, K Madhava
Efficiently generating grasp poses tailored to specific regions of an object is vital for various robotic manipulation tasks, especially in a dual-arm setup. This scenario presents a significant challenge due to the complex geometries involved, requi
Externí odkaz:
http://arxiv.org/abs/2404.04643
Inspired by cognitive theories, we introduce AnyHome, a framework that translates any text into well-structured and textured indoor scenes at a house-scale. By prompting Large Language Models (LLMs) with designed templates, our approach converts prov
Externí odkaz:
http://arxiv.org/abs/2312.06644