Dense Subgraph Maintenance under Streaming Edge Weight Updates for Real-time Story Identification Albert Angel Nick Koudas

Source URL: vldb.org

Real-Time Visual Odometry from Dense RGB-D Images Frank Steinbrücker Jürgen Sturm Daniel Cremers Department of Computer Science, Technical University of Munich, Germany {steinbrf,sturmju,cremers}@in.tum.de

Source URL: vision.in.tum.de

Real-Time Dense Geometry from a Handheld Camera Jan St¨ uhmer1,2 , Stefan Gumhold2 , and Daniel Cremers1 1 2

Source URL: vision.in.tum.de

Monitoring Dense-Time, Continuous-Semantics, Metric Temporal Logic Kevin Baldor 1,2

Source URL: rv2012.ku.edu.tr

• Distributed computing
• Safety
• United States federal banking legislation
• Liveness
• GrammLeachBliley Act
• Gramm
• Model checking
• Computing

Innovations in Water Monitoring In-Situ® Rentals Real-Time Measurement Technologies for

Source URL: in-situ.com

• Water
• Natural environment
• Biology
• Ecological restoration
• Hydrogeology
• Hydraulic engineering
• Hydrology
• Soil contamination
• Air sparging
• Environmental remediation
• Groundwater remediation
• Dense non-aqueous phase liquid

Towards Discrete-Time Verification of Time Petri Nets with Dense-Time Semantics? Agata Janowska1 , Wojciech Penczek2 , Agata P´olrola3 , and Andrzej Zbrzezny4 1 4

Source URL: csp2011.mimuw.edu.pl

2. Effective Approximations of Matching Priors 1. Summary How can we achieve truly robust dense, real-time matching? The strong priors generally available on image correspondence problems, are often used partially and p

Source URL: www.margaritachli.com

• Statistics
• Mathematics
• Random sample consensus
• SRI International
• Matching

A Primal-Dual Framework for Real-Time Dense RGB-D Scene Flow Mariano Jaimez1,2 , Mohamed Souiai2 , Javier Gonzalez-Jimenez1 and Daniel Cremers2 Abstract— This paper presents the first method to compute dense scene flow

Source URL: vision.in.tum.de

Polynomial Time Approximation S hemes for Dense and Geometri k-Restri ted Forest Problems

Source URL: theory.cs.uni-bonn.de

Dense Continuous-Time Tracking and Mapping with Rolling Shutter RGB-D Cameras Supplementary Material Christian Kerl, J¨org St¨uckler, and Daniel Cremers Technische Universit¨at M¨unchen {kerl,stueckle,cremers}@in.tum

Source URL: vision.in.tum.de