Zobrazeno 1 - 10
of 9 388
pro vyhledávání: '"Deva, A."'
Autor:
Gare, Gautam, Armouti, Jana, Madaan, Nikhil, Panda, Rohan, Fox, Tom, Hutchins, Laura, Krishnan, Amita, Rodriguez, Ricardo, DeBoisblanc, Bennett, Ramanan, Deva, Galeotti, John
A crucial question in active patient care is determining if a treatment is having the desired effect, especially when changes are subtle over short periods. We propose using inter-patient data to train models that can learn to detect these fine-grain
Externí odkaz:
http://arxiv.org/abs/2411.01144
Autor:
Li, Baiqi, Lin, Zhiqiu, Peng, Wenxuan, Nyandwi, Jean de Dieu, Jiang, Daniel, Ma, Zixian, Khanuja, Simran, Krishna, Ranjay, Neubig, Graham, Ramanan, Deva
Vision-language models (VLMs) have made significant progress in recent visual-question-answering (VQA) benchmarks that evaluate complex visio-linguistic reasoning. However, are these models truly effective? In this work, we show that VLMs still strug
Externí odkaz:
http://arxiv.org/abs/2410.14669
In this paper, we explore how performers' embodied interactions with a Neural Audio Synthesis model allow the exploration of the latent space of such a model, mediated through movements sensed by e-textiles. We provide background and context for the
Externí odkaz:
http://arxiv.org/abs/2410.14590
Autor:
Vedder, Kyle, Peri, Neehar, Khatri, Ishan, Li, Siyi, Eaton, Eric, Kocamaz, Mehmet, Wang, Yue, Yu, Zhiding, Ramanan, Deva, Pehserl, Joachim
We reframe scene flow as the task of estimating a continuous space-time ODE that describes motion for an entire observation sequence, represented with a neural prior. Our method, EulerFlow, optimizes this neural prior estimate against several multi-o
Externí odkaz:
http://arxiv.org/abs/2410.02031
We present a method to reconstruct time-consistent human body models from monocular videos, focusing on extremely loose clothing or handheld object interactions. Prior work in human reconstruction is either limited to tight clothing with no object in
Externí odkaz:
http://arxiv.org/abs/2409.20563
Autor:
Bull, J. Mark, Coughtrie, Andrew, Deeptimahanti, Deva, Hedley, Mark, Laoide-Kemp, Caoimhín, Maynard, Christopher, Shepherd, Harry, van de Bund, Sebastiaan, Weiland, Michèle, Went, Benjamin
This study presents scaling results and a performance analysis across different supercomputers and compilers for the Met Office weather and climate model, LFRic. The model is shown to scale to large numbers of nodes which meets the design criteria, t
Externí odkaz:
http://arxiv.org/abs/2409.15859
Autor:
Chakravarthy, Anirudh S, Ganesina, Meghana Reddy, Hu, Peiyun, Leal-Taixe, Laura, Kong, Shu, Ramanan, Deva, Osep, Aljosa
Addressing Lidar Panoptic Segmentation (LPS ) is crucial for safe deployment of autonomous vehicles. LPS aims to recognize and segment lidar points w.r.t. a pre-defined vocabulary of semantic classes, including thing classes of countable objects (e.g
Externí odkaz:
http://arxiv.org/abs/2409.14273
Reconstructing scenes and tracking motion are two sides of the same coin. Tracking points allow for geometric reconstruction [14], while geometric reconstruction of (dynamic) scenes allows for 3D tracking of points over time [24, 39]. The latter was
Externí odkaz:
http://arxiv.org/abs/2409.02104
Autor:
Saba, Andrew, Adetunji, Aderotimi, Johnson, Adam, Kothari, Aadi, Sivaprakasam, Matthew, Spisak, Joshua, Bharatia, Prem, Chauhan, Arjun, Duff Jr., Brendan, Gasparro, Noah, King, Charles, Larkin, Ryan, Mao, Brian, Nye, Micah, Parashar, Anjali, Attias, Joseph, Balciunas, Aurimas, Brown, Austin, Chang, Chris, Gao, Ming, Heredia, Cindy, Keats, Andrew, Lavariega, Jose, Muckelroy III, William, Slavescu, Andre, Stathas, Nickolas, Suvarna, Nayana, Zhang, Chuan Tian, Scherer, Sebastian, Ramanan, Deva
Publikováno v:
Field Robotics Volume 4 (2024) 1-45
Autonomous motorsports aim to replicate the human racecar driver with software and sensors. As in traditional motorsports, Autonomous Racing Vehicles (ARVs) are pushed to their handling limits in multi-agent scenarios at extremely high ($\geq 150mph$
Externí odkaz:
http://arxiv.org/abs/2408.15425
In this paper, we present a method for dynamic surface reconstruction of large-scale urban scenes from LiDAR. Depth-based reconstructions tend to focus on small-scale objects or large-scale SLAM reconstructions that treat moving objects as outliers.
Externí odkaz:
http://arxiv.org/abs/2406.13896