Zobrazeno 1 - 10
of 1 806
pro vyhledávání: '"Agrawala A"'
Scriptwriters usually rely on their mental visualization to create a vivid story by using their imagination to see, feel, and experience the scenes they are writing. Besides mental visualization, they often refer to existing images or scenes in movie
Externí odkaz:
http://arxiv.org/abs/2410.03224
Autor:
Woodman, Stephanie J., Shah, Dylan S., Landesberg, Melanie, Agrawala, Anjali, Kramer-Bottiglio, Rebecca
Publikováno v:
Science Robotics, Vol 9, Issue 94, 2024
To achieve real-world functionality, robots must have the ability to carry out decision-making computations. However, soft robots stretch and therefore need a solution other than rigid computers. Examples of embedding computing capacity into soft rob
Externí odkaz:
http://arxiv.org/abs/2409.10333
Autor:
Liu, Hsueh-Ti Derek, Agrawala, Maneesh, Yuksel, Cem, Omernick, Tim, Misra, Vinith, Corazza, Stefano, McGuire, Morgan, Zordan, Victor
This paper presents a unified differentiable boolean operator for implicit solid shape modeling using Constructive Solid Geometry (CSG). Traditional CSG relies on min, max operators to perform boolean operations on implicit shapes. But because these
Externí odkaz:
http://arxiv.org/abs/2407.10954
We introduce a novel sketch-to-image tool that aligns with the iterative refinement process of artists. Our tool lets users sketch blocking strokes to coarsely represent the placement and form of objects and detail strokes to refine their shape and s
Externí odkaz:
http://arxiv.org/abs/2402.18116
Autor:
Zhang, Lvmin, Agrawala, Maneesh
We present LayerDiffuse, an approach enabling large-scale pretrained latent diffusion models to generate transparent images. The method allows generation of single transparent images or of multiple transparent layers. The method learns a "latent tran
Externí odkaz:
http://arxiv.org/abs/2402.17113
Autor:
Deng, Kangle, Omernick, Timothy, Weiss, Alexander, Ramanan, Deva, Zhu, Jun-Yan, Zhou, Tinghui, Agrawala, Maneesh
Manually creating textures for 3D meshes is time-consuming, even for expert visual content creators. We propose a fast approach for automatically texturing an input 3D mesh based on a user-provided text prompt. Importantly, our approach disentangles
Externí odkaz:
http://arxiv.org/abs/2402.13251
Authors often add text annotations to charts to provide additional context for visually prominent features such as peaks, valleys, and trends. However, writing annotations that provide contextual information, such as descriptions of temporal events,
Externí odkaz:
http://arxiv.org/abs/2312.03278
Motion graphics videos are widely used in Web design, digital advertising, animated logos and film title sequences, to capture a viewer's attention. But editing such video is challenging because the video provides a low-level sequence of pixels and f
Externí odkaz:
http://arxiv.org/abs/2309.14642
Autor:
Subramonyam, Hariharan, Pea, Roy, Pondoc, Christopher Lawrence, Agrawala, Maneesh, Seifert, Colleen
Large language models (LLMs) exhibit dynamic capabilities and appear to comprehend complex and ambiguous natural language prompts. However, calibrating LLM interactions is challenging for interface designers and end-users alike. A central issue is ou
Externí odkaz:
http://arxiv.org/abs/2309.14459
We study inferring a tree-structured representation from a single image for object shading. Prior work typically uses the parametric or measured representation to model shading, which is neither interpretable nor easily editable. We propose using the
Externí odkaz:
http://arxiv.org/abs/2309.07122