Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Muhle, Dominik"'
Inferring scene geometry from images via Structure from Motion is a long-standing and fundamental problem in computer vision. While classical approaches and, more recently, depth map predictions only focus on the visible parts of a scene, the task of
Externí odkaz:
http://arxiv.org/abs/2404.07933
Autor:
Saroha, Abhishek, Gladkova, Mariia, Curreli, Cecilia, Muhle, Dominik, Yenamandra, Tarun, Cremers, Daniel
3D scene stylization extends the work of neural style transfer to 3D. A vital challenge in this problem is to maintain the uniformity of the stylized appearance across multiple views. A vast majority of the previous works achieve this by training a 3
Externí odkaz:
http://arxiv.org/abs/2403.08498
3D semantic scene understanding is a fundamental challenge in computer vision. It enables mobile agents to autonomously plan and navigate arbitrary environments. SSC formalizes this challenge as jointly estimating dense geometry and semantic informat
Externí odkaz:
http://arxiv.org/abs/2310.07522
We propose a differentiable nonlinear least squares framework to account for uncertainty in relative pose estimation from feature correspondences. Specifically, we introduce a symmetric version of the probabilistic normal epipolar constraint, and an
Externí odkaz:
http://arxiv.org/abs/2305.09527
The estimation of the relative pose of two camera views is a fundamental problem in computer vision. Kneip et al. proposed to solve this problem by introducing the normal epipolar constraint (NEC). However, their approach does not take into account u
Externí odkaz:
http://arxiv.org/abs/2204.02256