Sminchisescu, C.[Cristian]
* 2001: Covariance Scaled Sampling for Monocular 3D Body Tracking
* 2001: Framework for Generic State Estimation in Computer Vision Applications, A
* 2001: Improving the Scope of Deformable Model Shape and Motion Estimation
* 2001: Incremental Model-Based Estimation Using Geometric Consistency Constraints
* 2001: Robust Multiple Hypothesis Approach to Monocular Human Motion Tracking, A
* 2002: Building Roadmaps of Local Minima of Visual Models
* 2002: Human Pose Estimation from Silhouettes: A Consistent Approach Using Distance Level Sets
* 2002: Hyperdynamics Importance Sampling
* 2003: Kinematic jump processes for monocular 3D human tracking
* 2004: Optimal inference for hierarchical skeleton abstraction
* 2004: Variational mixture smoothing for non-linear dynamical systems
* 2005: Building Roadmaps of Minima and Transitions in Visual Models
* 2005: Conditional Random Fields for Contextual Human Motion Recognition
* 2005: Discriminative Density Propagation for 3D Human Motion Estimation
* 2005: Incremental Model-Based Estimation Using Geometric Constraints
* 2005: Learning Hierarchical Shape Models from Examples
* 2006: 3D Human Motion Analysis in Monocular Video Techniques and Challenges
* 2006: Canonical Skeletons for Shape Matching
* 2006: Conditional models for contextual human motion recognition
* 2006: Fast mixing hyperdynamic sampling
* 2006: Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
* 2006: Training Deformable Models for Localization
* 2007: BM³E : Discriminative Density Propagation for Visual Tracking
* 2007: Semi-supervised Hierarchical Models for 3D Human Pose Reconstruction
* 2007: Spectral Latent Variable Models for Perceptual Inference
* 2007: Support Kernel Machines for Object Recognition
* 2008: 3D Human Motion Analysis in Monocular Video Techniques and Challenges
* 2008: Fast algorithms for large scale conditional 3D prediction
* 2009: Multiscale Symmetric Part Detection and Grouping
* 2009: Selection and context for action recognition
* 2009: Structural SVM for visual localization and continuous state estimation
* 2009: Structured output-associative regression
* 2010: Constrained parametric min-cuts for automatic object segmentation
* 2010: Object recognition as ranking holistic figure-ground hypotheses
* 2010: Optimal Contour Closure by Superpixel Grouping
* 2010: Random Fourier Approximations for Skewed Multiplicative Histogram Kernels
* 2010: Spatiotemporal Closure
* 2010: Twin Gaussian Processes for Structured Prediction
* 2011: Generalized darting Monte Carlo
* 2011: Image segmentation by figure-ground composition into maximal cliques
* 2011: Latent structured models for human pose estimation
* 2011: Semi-supervised learning and optimization for hypergraph matching
* 2012: Chebyshev approximations to the histogram X^2 kernel
* 2012: CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts
* 2012: Dynamic Eye Movement Datasets and Learnt Saliency Models for Visual Action Recognition
* 2012: Efficient Closed-Form Solution to Generalized Boundary Detection
* 2012: Fourier Kernel Learning
* 2012: Object Recognition by Sequential Figure-Ground Ranking
* 2012: Optimal Image and Video Closure by Superpixel Grouping
* 2012: Perceptual Grouping Using Superpixels
* 2012: Semantic Segmentation with Second-Order Pooling
* 2013: Composite Statistical Inference for Semantic Segmentation
* 2013: Locally Affine Sparse-to-Dense Matching for Motion and Occlusion Estimation
* 2013: Moving Pose: An Efficient 3D Kinematics Descriptor for Low-Latency Action Recognition and Detection, The
* 2013: Multiscale Symmetric Part Detection and Grouping
* 2013: Pictorial Human Spaces: How Well Do Humans Perceive a 3D Articulated Pose?
* 2013: Video Object Segmentation by Salient Segment Chain Composition
* 2014: Generalized Boundaries from Multiple Image Interpretations
* 2014: Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments
* 2014: Iterated Second-Order Label Sensitive Pooling for 3D Human Pose Estimation
* 2014: Probabilistic Joint Image Segmentation and Labeling by Figure-Ground Composition
* 2015: Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition
* 2015: Free-Form Region Description with Second-Order Pooling
* 2015: Large Displacement 3D Scene Flow with Occlusion Reasoning
* 2015: Matrix Backpropagation for Deep Networks with Structured Layers
* 2015: Second-order constrained parametric proposals and sequential search-based structured prediction for semantic segmentation in RGB-D images
* 2016: Parametric Image Segmentation of Humans with Structural Shape Priors
* 2016: Pictorial Human Spaces: A Computational Study on the Human Perception of 3D Articulated Poses
* 2016: Reinforcement Learning for Visual Object Detection
* 2016: Spatio-Temporal Attention Models for Grounded Video Captioning
* 2017: Deep Multitask Architecture for Integrated 2D and 3D Human Sensing
* 2018: 3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children with Autism
* 2018: Deep Learning of Graph Matching
* 2018: Deep Reinforcement Learning of Region Proposal Networks for Object Detection
* 2018: Human Appearance Transfer
* 2018: Monocular 3D Pose and Shape Estimation of Multiple People in Natural Scenes: The Importance of Multiple Scene Constraints
* 2018: Semantic Video Segmentation by Gated Recurrent Flow Propagation
* 2019: Self-Supervised Learning With Geometric Constraints in Monocular Video: Connecting Flow, Depth, and Camera
* 2020: Combining Implicit Function Learning and Parametric Models for 3d Human Reconstruction
* 2020: Consistency Guided Scene Flow Estimation
* 2020: GHUM GHUML: Generative 3D Human Shape and Articulated Pose Models
* 2020: Semantic Synthesis of Pedestrian Locomotion
* 2020: Special Issue: Advances in Architectures and Theories for Computer Vision
* 2020: Three-Dimensional Reconstruction of Human Interactions
* 2020: Weakly Supervised 3d Human Pose and Shape Reconstruction with Normalizing Flows
* 2021: AIFit: Automatic 3D Human-Interpretable Feedback Models for Fitness Training
* 2021: imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Pose
* 2021: Neural Descent for Visual 3D Human Pose and Shape
* 2021: RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection
* 2021: THUNDR: Transformer-based 3D HUmaN Reconstruction with Markers
* 2022: BEHAVE: Dataset and Method for Tracking Human Object Interactions
* 2022: Differentiable Dynamics for Articulated 3d Human Motion Reconstruction
* 2022: ERA: Enhanced Rational Activations
* 2022: Learning Online Multi-Sensor Depth Fusion
* 2022: Photorealistic Monocular 3D Reconstruction of Humans Wearing Clothing
* 2022: Trajectory Optimization for Physics-Based Reconstruction of 3d Human Pose from Monocular Video
* 2023: Structured 3D Features for Reconstructing Controllable Avatars
* 2023: Transformer-Based Learned Optimization
Includes: Sminchisescu, C.[Cristian] Sminchisescu, C.
98 for Sminchisescu, C.
Smink, K.[Karl]
* 2019: New Traversal Method for Virtual Reality:, A
Smink, M.[Moniek]
* 2024: Computer Vision on the Edge: Individual Cattle Identification in Real-time with ReadMyCow System