Memin, A.[Anthony]
* 2021: Inter-Annual Variability in the Antarctic Ice Sheets Using Geodetic Observations and a Climate Model
Includes: Memin, A.[Anthony] Mémin, A.[Anthony]
Memin, E.
* 1994: Efficient Parallel Multigrid Relaxation Algorithms for Markov Random Field-Based Low-Level Vision Applications
* 1996: Parallelized Robust Multiresolution Motion Estimation
* 1996: Robust Discontinuity-Preserving Model for Estimating Optical Flow
* 1998: Dense Estimation and Object-Based Segmentation of the Optical-Flow with Robust Techniques
* 1998: Joint Estimation-Segmentation of Optic Flow
* 1998: Multigrid Approach for Hierarchical Motion Estimation, A
* 1998: Planar facets segmentation using a multiresolution dense disparity field estimation
* 1999: Dense/Parametric Estimation of Fluid Flows
* 2000: Energy-based Framework for Dense 3D Registration of Volumetric Brain Images, An
* 2000: Estimating Fluid Optical Flow
* 2000: Geometric Driven Optical Flow Estimation and Segmentation for 3D Reconstruction
* 2000: Tracking and Characterization of Highly Deformable Cloud Structures
* 2001: Hierarchical estimation of a dense deformation field for 3-D robust registration
* 2001: VLSI Design Methodology for Edge-Preserving Image Reconstruction
* 2002: Dense Estimation of Fluid Flows
* 2002: Dense Motion Analysis in Fluid Imagery
* 2002: Hierarchical Estimation and Segmentation of Dense Motion Fields
* 2003: Extraction of Singular Points from Dense Motion Fields: An Analytic Approach
* 2003: One-dimensional dense disparity estimation for three-dimensional reconstruction
* 2003: Robust Multiscale Deformable Registration of 3d Ultrasound Images
* 2003: Variational Dense Motion Estimation Using the Helmholtz Decomposition
* 2004: Course to Fine Multiscale Approach for Linear Least Squares Optical Flow Estimation, A
* 2004: Optimal Importance Sampling for Tracking in Image Sequences: Application to Point Tracking
* 2005: Conditional Filters for Image Sequence-Based Tracking: Application to Point Tracking
* 2005: Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation
* 2005: Model Free Hybrid Algorithm for Real Time Tracking, A
* 2005: Robust and Automatic Face Tracker Dedicated to Broadcast Videos, A
* 2005: Stochastic Filter for Fluid Motion Tracking, A
* 2005: Vortex and Source Particles for Fluid Motion Estimation
* 2006: Dense Estimation of Layer Motions in the Atmosphere
* 2006: Fluid Motion Estimator for Schlieren Image Velocimetry, A
* 2007: Consistent Spatio-temporal Motion Estimator for Atmospheric Layers, A
* 2007: Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation
* 2007: Dynamically consistent optical flow estimation
* 2007: Image Assimilation for Motion Estimation of Atmospheric Layers with Shallow-Water Model
* 2007: Low Dimensional Fluid Motion Estimator, A
* 2007: Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
* 2007: Variational Framework for Spatio-temporal Smoothing of Fluid Motions, A
* 2007: Variational optimal control technique for the tracking of deformable objects
* 2008: Hybrid tracking approach using optical flow and pose estimation
* 2008: Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
* 2008: Self-similar regularization of optic-flow for turbulent motion estimation
* 2008: Three-Dimensional Motion Estimation of Atmospheric Layers From Image Sequences
* 2008: Variational Assimilation Of Fluid Motion From Image Sequence
* 2008: Variational Technique for Time Consistent Tracking of Curves and Motion, A
* 2009: Bayesian selection of scaling laws for motion modeling in images
* 2009: Stochastic Filtering Technique for Fluid Flow Velocity Fields Tracking, A
* 2009: Tracking Closed Curves with Non-linear Stochastic Filters
* 2010: Stochastic Filtering of Level Sets for Curve Tracking
* 2011: Multiscale Weighted Ensemble Kalman Filter for Fluid Flow Estimation
* 2011: Robust Optic-Flow Estimation with Bayesian Inference of Model and Hyper-parameters
* 2011: Stochastic Models for Local Optical Flow Estimation
* 2011: Wavelet-Based Fluid Motion Estimation
* 2012: Bayesian Inference of Models and Hyperparameters for Robust Optical-Flow Estimation
* 2012: Stochastic Uncertainty Models for the Luminance Consistency Assumption
* 2013: Bayesian Estimation of Turbulent Motion
* 2013: Divergence-Free Wavelets and High Order Regularization
* 2014: Stochastic Level Set Dynamics to Track Closed Curves Through Image Data
* 2017: Location Uncertainty Principle: Toward the Definition of Parameter-Free Motion Estimators
Includes: Memin, E. Memin, E.[Etienne] Mémin, É.[Étienne] Mémin, E.[Etienne] Mémin, E.
59 for Memin, E.
Memis, A.[Abbas]
* 2025: Automatic Turkish Image Captioning Using Non-Native Deep Caption Generator Models and Neural Machine Translators
Memisevic, R.
* 2005: Principal Surfaces from Unsupervised Kernel Regression
* 2007: Unsupervised Learning of Image Transformations
* 2009: Shared Kernel Information Embedding for Discriminative Inference
* 2011: Gradient-based learning of higher-order image features
* 2011: Modeling the joint density of two images under a variety of transformations
* 2012: Shared Kernel Information Embedding for Discriminative Inference
* 2013: Learning to Relate Images
* 2015: Potential Energy of an Autoencoder, The
* 2017: RATM: Recurrent Attentive Tracking Model
* 2017: Something Something Video Database for Learning and Evaluating Visual Common Sense, The
* 2018: Hierarchical Video Understanding
* 2019: Jester Dataset: A Large-Scale Video Dataset of Human Gestures, The
* 2023: Painter: Teaching Auto-regressive Language Models to Draw Sketches
Includes: Memisevic, R. Memisevic, R.[Roland]
13 for Memisevic, R.
Memisoglu, A.[Aydemir]
* 2007: Motion Control for Realistic Walking Behavior using Inverse Kinematics