Index for szna

Sznaier, M.[Mario] Co Author Listing * Activity recognition using dynamic subspace angles
* Caratheodory-Fejer Approach to Dynamic Appearance Modeling, A
* Caratheodory-Fejer Approach to Robust Multiframe Tracking, A
* convex optimization approach to robust fundamental matrix estimation, A
* Cross-view activity recognition using Hankelets
* DYAN: A Dynamical Atoms-Based Network for Video Prediction
* Dynamic Appearance Modeling for Human Tracking
* Dynamic Context for Tracking behind Occlusions
* Dynamic subspace-based coordinated multicamera tracking
* Dynamics Based Robust Motion Segmentation
* Dynamics Enhanced Multi-camera Motion Segmentation from Unsynchronized Videos
* Efficient Temporal Sequence Comparison and Classification Using Gram Matrix Embeddings on a Riemannian Manifold
* Euclidean Structure Recovery from Motion in Perspective Image Sequences via Hankel Rank Minimization
* Fast algorithms for structured robust principal component analysis
* Fast track matching and event detection
* Finding Causal Interactions in Video Sequences
* GPCA with denoising: A moments-based convex approach
* Jensen Bregman LogDet Divergence Optimal Filtering in the Manifold of Positive Definite Matrices
* Low order dynamics embedding for high dimensional time series
* Model (In)Validation Approach to Gait Classification, A
* model (In)validation approach to gait recognition, A
* moM: Mean of Moments Feature for Person Re-identification
* MoNet: Moments Embedding Network
* Person Re-identification in Appearance Impaired Scenarios
* Person Re-Identification Using Kernel-Based Metric Learning Methods
* Rank Minimization Approach to Video Inpainting, A
* Robust Structure from Motion and Identified Dynamics
* Segmentation for Robust Tracking in the Presence of Severe Occlusion
* Self Scaled Regularized Robust Regression
* Sequential sparsification for change detection
* Solving Temporal Puzzles
* SoS-RSC: A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms
* Subspace Clustering with Priors via Sparse Quadratically Constrained Quadratic Programming
* Way They Move: Tracking Multiple Targets with Similar Appearance, The
Includes: Sznaier, M.[Mario] Sznaier, M.
34 for Sznaier, M.

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