Zobrazeno 1 - 10
of 13 507
pro vyhledávání: '"A Cremers"'
Autor:
Weber, Mark, Yu, Lijun, Yu, Qihang, Deng, Xueqing, Shen, Xiaohui, Cremers, Daniel, Chen, Liang-Chieh
Masked transformer models for class-conditional image generation have become a compelling alternative to diffusion models. Typically comprising two stages - an initial VQGAN model for transitioning between latent space and image space, and a subseque
Externí odkaz:
http://arxiv.org/abs/2409.16211
Autor:
Cheng, Lei, Hu, Junpeng, Yan, Haodong, Gladkova, Mariia, Huang, Tianyu, Liu, Yun-Hui, Cremers, Daniel, Li, Haoang
Photometric bundle adjustment (PBA) is widely used in estimating the camera pose and 3D geometry by assuming a Lambertian world. However, the assumption of photometric consistency is often violated since the non-diffuse reflection is common in real-w
Externí odkaz:
http://arxiv.org/abs/2409.11854
Autor:
Cremers, Jolien, Kohler, Benjamin, Maier, Benjamin Frank, Eriksen, Stine Nymann, Einsiedler, Johanna, Christensen, Frederik Kølby, Lehmann, Sune, Lassen, David Dreyer, Mortensen, Laust Hvas, Bjerre-Nielsen, Andreas
Social networks shape individuals' lives, influencing everything from career paths to health. This paper presents a registry-based, multi-layer and temporal network of the entire Danish population in the years 2008-2021 (roughly 7.2 mill. individuals
Externí odkaz:
http://arxiv.org/abs/2409.11099
Contemporary research in autonomous driving has demonstrated tremendous potential in emulating the traits of human driving. However, they primarily cater to areas with well built road infrastructure and appropriate traffic management systems. Therefo
Externí odkaz:
http://arxiv.org/abs/2409.05119
Autor:
Yang, Linyan, Hoyer, Lukas, Weber, Mark, Fischer, Tobias, Dai, Dengxin, Leal-Taixé, Laura, Pollefeys, Marc, Cremers, Daniel, Van Gool, Luc
Unsupervised Domain Adaptation (UDA) is the task of bridging the domain gap between a labeled source domain, e.g., synthetic data, and an unlabeled target domain. We observe that current UDA methods show inferior results on fine structures and tend t
Externí odkaz:
http://arxiv.org/abs/2408.16478
Autor:
Zhou, Tianfei, Zhang, Fei, Chang, Boyu, Wang, Wenguan, Yuan, Ye, Konukoglu, Ender, Cremers, Daniel
Image segmentation is a long-standing challenge in computer vision, studied continuously over several decades, as evidenced by seminal algorithms such as N-Cut, FCN, and MaskFormer. With the advent of foundation models (FMs), contemporary segmentatio
Externí odkaz:
http://arxiv.org/abs/2408.12957
Autor:
Meier, Johannes, Scalerandi, Luca, Dhaouadi, Oussema, Kaiser, Jacques, Araslanov, Nikita, Cremers, Daniel
Existing techniques for monocular 3D detection have a serious restriction. They tend to perform well only on a limited set of benchmarks, faring well either on ego-centric car views or on traffic camera views, but rarely on both. To encourage progres
Externí odkaz:
http://arxiv.org/abs/2408.11958
We propose LiFCal, a novel geometric online calibration pipeline for MLA-based light field cameras. LiFCal accurately determines model parameters from a moving camera sequence without precise calibration targets, integrating arbitrary metric scaling
Externí odkaz:
http://arxiv.org/abs/2408.11682
Autor:
Bongratz, Fabian, Golkov, Vladimir, Mautner, Lukas, Della Libera, Luca, Heetmeyer, Frederik, Czaja, Felix, Rodemann, Julian, Cremers, Daniel
The field of reinforcement learning offers a large variety of concepts and methods to tackle sequential decision-making problems. This variety has become so large that choosing an algorithm for a task at hand can be challenging. In this work, we stre
Externí odkaz:
http://arxiv.org/abs/2407.20917
Neural implicit surfaces can be used to recover accurate 3D geometry from imperfect point clouds. In this work, we show that state-of-the-art techniques work by minimizing an approximation of a one-sided Chamfer distance. This shape metric is not sym
Externí odkaz:
http://arxiv.org/abs/2407.17058