Zobrazeno 1 - 10
of 477
pro vyhledávání: '"Iqbal Umar"'
Autor:
Parveze Mir Uzma, Mir Mohammad Maqbool, Rehman Munib Ur, Iqbal Umar, Khan Saba Q., Khan F. A., Khan Imran, Qayoom Sameera, Mushtaq Irtiqa, Shah Hamiyah K., Gaafar Abdel-Rhman Z., Kaushik Prashant
Publikováno v:
Folia Horticulturae, Vol 36, Iss 2, Pp 311-321 (2024)
Self-fertile cultivars of sweet cherry (Prunus avium) produce heavy crop load that is often associated with small and poor-quality fruits. Therefore, a crop load-management strategy is required to improve the quality of the fruit. In this study, the
Externí odkaz:
https://doaj.org/article/ab595baf9edb4896a290296bb677a133
Autor:
Li, Jiefeng, Yuan, Ye, Rempe, Davis, Zhang, Haotian, Molchanov, Pavlo, Lu, Cewu, Kautz, Jan, Iqbal, Umar
Estimating global human motion from moving cameras is challenging due to the entanglement of human and camera motions. To mitigate the ambiguity, existing methods leverage learned human motion priors, which however often result in oversmoothed motion
Externí odkaz:
http://arxiv.org/abs/2408.16426
LLM app ecosystems are quickly maturing and supporting a wide range of use cases, which requires them to collect excessive user data. Given that the LLM apps are developed by third-parties and that anecdotal evidence suggests LLM platforms currently
Externí odkaz:
http://arxiv.org/abs/2408.13247
Large language models (LLMs) extended as systems, such as ChatGPT, have begun supporting third-party applications. These LLM apps leverage the de facto natural language-based automated execution paradigm of LLMs: that is, apps and their interactions
Externí odkaz:
http://arxiv.org/abs/2403.04960
Autor:
Petrovich, Mathis, Litany, Or, Iqbal, Umar, Black, Michael J., Varol, Gül, Peng, Xue Bin, Rempe, Davis
Recent advances in generative modeling have led to promising progress on synthesizing 3D human motion from text, with methods that can generate character animations from short prompts and specified durations. However, using a single text prompt as in
Externí odkaz:
http://arxiv.org/abs/2401.08559
Autor:
Trevithick, Alex, Chan, Matthew, Takikawa, Towaki, Iqbal, Umar, De Mello, Shalini, Chandraker, Manmohan, Ramamoorthi, Ravi, Nagano, Koki
3D-aware Generative Adversarial Networks (GANs) have shown remarkable progress in learning to generate multi-view-consistent images and 3D geometries of scenes from collections of 2D images via neural volume rendering. Yet, the significant memory and
Externí odkaz:
http://arxiv.org/abs/2401.02411
Autor:
Yuan, Ye, Li, Xueting, Huang, Yangyi, De Mello, Shalini, Nagano, Koki, Kautz, Jan, Iqbal, Umar
Gaussian splatting has emerged as a powerful 3D representation that harnesses the advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper, we seek to leverage Gaussian splatting to generate realistic animatable avatar
Externí odkaz:
http://arxiv.org/abs/2312.11461
Autor:
Kocabas, Muhammed, Yuan, Ye, Molchanov, Pavlo, Guo, Yunrong, Black, Michael J., Hilliges, Otmar, Kautz, Jan, Iqbal, Umar
We present a method to estimate human motion in a global scene from moving cameras. This is a highly challenging task due to the coupling of human and camera motions in the video. To address this problem, we propose a joint optimization framework tha
Externí odkaz:
http://arxiv.org/abs/2310.13768
Large language model (LLM) platforms, such as ChatGPT, have recently begun offering an app ecosystem to interface with third-party services on the internet. While these apps extend the capabilities of LLM platforms, they are developed by arbitrary th
Externí odkaz:
http://arxiv.org/abs/2309.10254
While privacy-focused browsers have taken steps to block third-party cookies and mitigate browser fingerprinting, novel tracking techniques that can bypass existing countermeasures continue to emerge. Since trackers need to share information from the
Externí odkaz:
http://arxiv.org/abs/2308.03417