Mordan, T.
* 2016: WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks
* 2017: WILDCAT: Weakly Supervised Learning of Deep ConvNets for Image Classification, Pointwise Localization and Segmentation
* 2019: End-to-End Learning of Latent Deformable Part-Based Representations for Object Detection
* 2021: Learning Decoupled Representations for Human Pose Forecasting
* 2022: Detecting 32 Pedestrian Attributes for Autonomous Vehicles
* 2022: Shared Representation for Photorealistic Driving Simulators, A
Includes: Mordan, T. Mordan, T.[Taylor]
Mordang, J.
* 2018: Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization
Mordang, J.J.[Jan Jurre]
* 2017: Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets
Includes: Mordang, J.J.[Jan Jurre] Mordang, J.J.[Jan-Jurre]
Morde, A.[Ashutosh]
* 2002: Multimodal System for Accessing Driving Directions, A
* 2011: GPU enabled Smart Video Node
* 2012: Contextual video clip classification
* 2012: Enhanced event recognition in video using image quality assessment
* 2012: Learning a background model for change detection
Includes: Morde, A.[Ashutosh] Morde, A.
Mordechay, M.[Moran]
* 2025: Rethinking Compressive Sensing: A Compression Framework for Video Super-Resolution
Mordelet, F.
* 2014: bagging SVM to learn from positive and unlabeled examples, A
Mordido, G.
* 2020: microbatchGAN: Stimulating Diversity with Multi-Adversarial Discrimination
* 2020: Monte Carlo Gradient Quantization
* 2021: Assessing Image and Text Generation with Topological Analysis and Fuzzy Logic
Includes: Mordido, G. Mordido, G.[Gonçalo]
Mordini, E.[Emilio]
* 2023: Biometric privacy protection: What is this thing called privacy?
* 2023: Facilitating free travel in the Schengen area: A position paper by the European Association for Biometrics
Mordohai, P.[Philippos]
* 2001: First Order Tensor Voting and Application to 3-D Scale Analysis
* 2001: Inference of Segmented Overlapping Surfaces from Binocular and Multiple-View Stereo
* 2001: Integrated Tensor Voting in Multiple Scales for Shape Description in 3D
* 2002: Inference of Segmented Overlapping Surfaces from Binocular Stereo
* 2002: Perceptual grouping for multiple view stereo using tensor voting
* 2004: Dense multiple view stereo with general camera placement using tensor voting
* 2004: First order augmentation to tensor voting for boundary inference and multiscale analysis in 3d
* 2004: Junction Inference and Classification for Figure Completion using Tensor Voting
* 2004: Tensor Voting Framework, The
* 2005: Unsupervised dimensionality estimation and manifold learning in high-dimensional spaces by tensor voting
* 2006: Simplified Belief Propagation for Multiple View Reconstruction
* 2006: Stereo Using Monocular Cues within the Tensor Voting Framework
* 2006: Tensor Voting: A Perceptual Organization Approach to Computer Vision and Machine Learning
* 2006: Towards Urban 3D Reconstruction from Video
* 2007: Evaluation of Large Scale Scene Reconstruction
* 2007: Multi-View Stereo via Graph Cuts on the Dual of an Adaptive Tetrahedral Mesh
* 2007: Real-Time Plane-Sweeping Stereo with Multiple Sweeping Directions
* 2007: Real-Time Visibility-Based Fusion of Depth Maps
* 2007: Temporally Consistent Reconstruction from Multiple Video Streams Using Enhanced Belief Propagation
* 2008: Detailed Real-Time Urban 3D Reconstruction from Video
* 2008: Object Detection from Large-Scale 3D Datasets Using Bottom-Up and Top-Down Descriptors
* 2008: Variable baseline/resolution stereo
* 2009: minimum cover approach for extracting the road network from airborne LIDAR data, A
* 2009: Self-Aware Matching Measure for stereo, The
* 2010: Automatic Facial Expression Recognition using Bags of Motion Words
* 2010: Detecting and parsing architecture at city scale from range data
* 2010: Evaluation of stereo confidence indoors and outdoors
* 2012: Least Commitment, Viewpoint-Based, Multi-view Stereo
* 2012: On the Evaluation of Scene Flow Estimation
* 2012: Quantitative Evaluation of Confidence Measures for Stereo Vision, A
* 2012: Robust Probabilistic Occupancy Grid Estimation from Positive and Negative Distance Fields
* 2014: 3D Interest Point Detection via Discriminative Learning
* 2014: Classification of Vehicle Parts in Unstructured 3D Point Clouds
* 2014: Egocentric Object Recognition Leveraging the 3D Shape of the Grasping Hand
* 2014: Learning to Detect Ground Control Points for Improving the Accuracy of Stereo Matching
* 2015: Exact bias correction and covariance estimation for stereo vision
* 2016: Correctness Prediction, Accuracy Improvement and Generalization of Stereo Matching Using Supervised Learning
* 2016: Correspondence estimation for non-rigid point clouds with automatic part discovery
* 2017: Shared Autonomy Approach for Wheelchair Navigation Based on Learned User Preferences, A
* 2017: Special Issue on Large-Scale 3D Modeling of Urban Indoor or Outdoor Scenes from Images and Range Scans
* 2018: CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation
* 2018: RecResNet: A Recurrent Residual CNN Architecture for Disparity Map Enhancement
* 2019: Learning to Navigate Robotic Wheelchairs from Demonstration: Is Training in Simulation Viable?
* 2020: Do End-to-end Stereo Algorithms Under-utilize Information?
* 2020: Matching-space Stereo Networks for Cross-domain Generalization
* 2021: Inlier clustering based on the residuals of random hypotheses
* 2022: On the Synergies Between Machine Learning and Binocular Stereo for Depth Estimation From Images: A Survey
* 2022: Single-camera 3D head fitting for mixed reality clinical applications
* 2023: Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty Estimation
* 2023: PRN: Panoptic Refinement Network
* 2023: V-FUSE: Volumetric Depth Map Fusion with Long-Range Constraints
* 2025: Glissando-Net: Deep Single View Category Level Pose Estimation and 3D Reconstruction
Includes: Mordohai, P.[Philippos] Mordohai, P.
52 for Mordohai, P.
Mordonini, M.
* 1999: Cellular automata-based optical flow computation for just-in-time applications
* 1999: Just-in-time Landmarks Recognition
* 2005: Evolving Binary Classifiers Through Parallel Computation of Multiple Fitness Cases
* 2007: Hybrid Stereo Sensor with Omnidirectional Vision Capabilities: Overview and Calibration Procedures
* 2007: Particle Swarm Optimization for Object Detection and Segmentation
* 2015: embedded architecture for real-time object detection in digital images based on niching particle swarm optimization, An
* 2015: Using Small Checkerboards as Size Reference: A Model-Based Approach
Includes: Mordonini, M. Mordonini, M.[Monica]
7 for Mordonini, M.
Mordvintsev, A.
* 2017: Associative Domain Adaptation
* 2017: Learning by Association: A Versatile Semi-Supervised Training Method for Neural Networks
Mordy, C.W.[Calvin W.]
* 2022: Sea Surface Salinity Variability in the Bering Sea in 2015-2020