Zobrazeno 1 - 10
of 8 132
pro vyhledávání: '"Vora, P"'
This paper presents a novel approach for cross-view synthesis aimed at generating plausible ground-level images from corresponding satellite imagery or vice versa. We refer to these tasks as satellite-to-ground (Sat2Grd) and ground-to-satellite (Grd2
Externí odkaz:
http://arxiv.org/abs/2412.03315
Many real-world sequential repair problems can be effectively modeled using monotonic Markov Decision Processes (MDPs), where the system state stochastically decreases and can only be increased by performing a restorative action. This work addresses
Externí odkaz:
http://arxiv.org/abs/2410.21249
The increasing reliance on diffusion models for generating synthetic images has amplified concerns about the unauthorized use of personal data, particularly facial images, in model training. In this paper, we introduce a novel identity inference fram
Externí odkaz:
http://arxiv.org/abs/2410.10177
In the context of axion search with haloscopes, tunable cavity resonators with high quality factor and high effective volume at frequencies above about 8 GHz are central for probing the axion-photon coupling with the required sensitivity to reach the
Externí odkaz:
http://arxiv.org/abs/2410.07774
Denoising diffusion models have emerged as state-of-the-art in generative tasks across image, audio, and video domains, producing high-quality, diverse, and contextually relevant data. However, their broader adoption is limited by high computational
Externí odkaz:
http://arxiv.org/abs/2409.13894
The ground-to-satellite image matching/retrieval was initially proposed for city-scale ground camera localization. This work addresses the problem of improving camera pose accuracy by ground-to-satellite image matching after a coarse location and ori
Externí odkaz:
http://arxiv.org/abs/2409.06471
Autor:
Vora, Pratik, Saha, Sudipan
Semantic segmentation is an important topic in computer vision with many relevant application in Earth observation. While supervised methods exist, the constraints of limited annotated data has encouraged development of unsupervised approaches. Howev
Externí odkaz:
http://arxiv.org/abs/2408.07393
Monotonic Partially Observable Markov Decision Processes (POMDPs), where the system state progressively decreases until a restorative action is performed, can be used to model sequential repair problems effectively. This paper considers the problem o
Externí odkaz:
http://arxiv.org/abs/2408.07192
Semantic segmentation has emerged as a pivotal area of study in computer vision, offering profound implications for scene understanding and elevating human-machine interactions across various domains. While 2D semantic segmentation has witnessed sign
Externí odkaz:
http://arxiv.org/abs/2407.16102
We introduce FedDM, a novel training framework designed for the federated training of diffusion models. Our theoretical analysis establishes the convergence of diffusion models when trained in a federated setting, presenting the specific conditions u
Externí odkaz:
http://arxiv.org/abs/2407.14730