Zobrazeno 1 - 10
of 3 416
pro vyhledávání: '"CZARNECKI, P."'
Autor:
Chen, Yuhao, He, Jiangpeng, Czarnecki, Chris, Vinod, Gautham, Mahmud, Talha Ibn, Raghavan, Siddeshwar, Ma, Jinge, Mao, Dayou, Nair, Saeejith, Xi, Pengcheng, Wong, Alexander, Delp, Edward, Zhu, Fengqing
Food computing is both important and challenging in computer vision (CV). It significantly contributes to the development of CV algorithms due to its frequent presence in datasets across various applications, ranging from classification and instance
Externí odkaz:
http://arxiv.org/abs/2409.01966
Current strategies for solving image-based inverse problems apply latent diffusion models to perform posterior sampling.However, almost all approaches make no explicit attempt to explore the solution space, instead drawing only a single sample from a
Externí odkaz:
http://arxiv.org/abs/2408.13868
Publikováno v:
Rules and Reasoning (2022) 263-279
Autonomous vehicles require highly sophisticated decision-making to determine their motion. This paper describes how such functionality can be achieved with a practical rule engine learned from expert driving decisions. We propose an algorithm to cre
Externí odkaz:
http://arxiv.org/abs/2407.00460
Ellipse estimation is an important topic in food image processing because it can be leveraged to parameterize plates and bowls, which in turn can be used to estimate camera view angles and food portion sizes. Automatically detecting the elliptical ri
Externí odkaz:
http://arxiv.org/abs/2405.07121
Monitoring dietary intake is a crucial aspect of promoting healthy living. In recent years, advances in computer vision technology have facilitated dietary intake monitoring through the use of images and depth cameras. However, the current state-of-t
Externí odkaz:
http://arxiv.org/abs/2405.08717
Autor:
Acharya, B., Aliotta, M., Balantekin, A. B., Bemmerer, D., Bertulani, C. A., Best, A., Brune, C. R., Buompane, R., Cavanna, F., Chen, J. W., Colgan, J., Czarnecki, A., Davids, B., deBoer, R. J., Delahaye, F., Depalo, R., García, A., Johnson, M. Gatu, Gazit, D., Gialanella, L., Greife, U., Guffanti, D., Guglielmetti, A., Hambleton, K., Haxton, W. C., Herrera, Y., Huang, M., Iliadis, C., Kravvaris, K., La Cognata, M., Langanke, K., Marcucci, L. E., Nagayama, T., Nollett, K. M., Odell, D., Gann, G. D. Orebi, Piatti, D., Pinsonneault, M., Platter, L., Robertson, R. G. H., Rupak, G., Serenelli, A., Sferrazza, M., Szücs, T., Tang, X., Tumino, A., Villante, F. L., Walker-Loud, A., Zhang, X., Zuber, K.
In stars that lie on the main sequence in the Hertzsprung Russel diagram, like our sun, hydrogen is fused to helium in a number of nuclear reaction chains and series, such as the proton-proton chain and the carbon-nitrogen-oxygen cycles. Precisely de
Externí odkaz:
http://arxiv.org/abs/2405.06470
With the increasing presence of autonomous vehicles (AVs) on public roads, developing robust control strategies to navigate the uncertainty of human-driven vehicles (HVs) is crucial. This paper introduces an advanced method for modeling HV behavior,
Externí odkaz:
http://arxiv.org/abs/2404.06732
Assessing Visually-Continuous Corruption Robustness of Neural Networks Relative to Human Performance
While Neural Networks (NNs) have surpassed human accuracy in image classification on ImageNet, they often lack robustness against image corruption, i.e., corruption robustness. Yet such robustness is seemingly effortless for human perception. In this
Externí odkaz:
http://arxiv.org/abs/2402.19401
This paper addresses motion forecasting in multi-agent environments, pivotal for ensuring safety of autonomous vehicles. Traditional as well as recent data-driven marginal trajectory prediction methods struggle to properly learn non-linear agent-to-a
Externí odkaz:
http://arxiv.org/abs/2401.07729
We consider the problem of cross-sensor domain adaptation in the context of LiDAR-based 3D object detection and propose Stationary Object Aggregation Pseudo-labelling (SOAP) to generate high quality pseudo-labels for stationary objects. In contrast t
Externí odkaz:
http://arxiv.org/abs/2401.04230