Koes, D.
* 2001: Precise Omnidirectional Camera Calibration
Koesdwiady, A.[Arief]
* 2017: End-to-End Deep Learning for Driver Distraction Recognition
Koeser, K.[Kevin]
* 2004: Dense Optic Flow with a Bayesian Occlusion Model
* 2006: Robust Feature Representation for Efficient Camera Registration
* 2007: Analysis-by-Synthesis Camera Tracking Approach Based on Free-Form Surfaces, An
* 2007: Extraction of 3D freeform surfaces as visual landmarks for real-time tracking
* 2007: Perspectively Invariant Normal Features
* 2007: Robust GPU-assisted camera tracking using free-form surface models
* 2008: Conjugate rotation: Parameterization and estimation from an affine feature correspondence
* 2008: Exploiting Uncertainty Propagation in Gradient-based Image Registration
* 2012: One-sided Radial-Fundamental Matrix Estimation
Includes: Koeser, K.[Kevin] Koeser, K.
9 for Koeser, K.
Koesmahargyo, V.[Vidya]
* 2021: Estimation of Clinical Tremor using Spatio-Temporal Adversarial AutoEncoder
Koester, C.J.
* 1965: Optical and Electro-Optical Info. Proc.
Koester, D.[Daniel]
* 2014: Way to Go! Detecting Open Areas Ahead of a Walking Person
* 2017: Mind the Gap: Virtual Shorelines for Blind and Partially Sighted People
* 2017: Using Technology Developed for Autonomous Cars to Help Navigate Blind People
Includes: Koester, D.[Daniel] Koester, D.
Koesters, T.
* 2017: Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer
Koestler, L.[Lukas]
* 2020: Learning Monocular 3D Vehicle Detection Without 3D Bounding Box Labels
* 2022: Intrinsic Neural Fields: Learning Functions on Manifolds
* 2022: Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions, The
* 2023: Learning Correspondence Uncertainty via Differentiable Nonlinear Least Squares
* 2023: Neural Implicit Representations for Physical Parameter Inference from a Single Video
* 2024: Masked Event Modeling: Self-Supervised Pretraining for Event Cameras