Hogg, A.[Anna]
* 2020: Arctic Sea Level Budget Assessment during the GRACE/Argo Time Period
Hogg, A.E.[Anna E.]
* 2018: Seasonal Variations in the Flow of Land-Terminating Glaciers in Central-West Greenland Using Sentinel-1 Imagery
* 2019: Sub-Annual Calving Front Migration, Area Change and Calving Rates from Swath Mode CryoSat-2 Altimetry, on Filchner-Ronne Ice Shelf, Antarctica
Hogg, D.[David]
* 2013: Domain Adaptation for Upper Body Pose Tracking in Signed TV Broadcasts
* 2013: Robust abandoned object detection integrating wide area visual surveillance and social context
* 2014: Upper Body Pose Estimation with Temporal Sequential Forests
* 2016: Personalizing Human Video Pose Estimation
* 2016: Virtual Immortality: Reanimating Characters from TV Shows
* 2021: Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack
* 2023: Horse with no Labels: Self-Supervised Horse Pose Estimation from Unlabelled Images and Synthetic Prior, A
* 2023: Of Mice and Pose: 2d Mouse Pose Estimation from Unlabelled Data and Synthetic Prior
* 2023: Self-supervised 3D Human Pose Estimation from a Single Image
9 for Hogg, D.
Hogg, D.C.
* 1977: Methodology for Real Time Scene Analysis, A
* 1983: Model-Based Vision: A Program to See a Walking Person
* 1986: Knowledge-Based Interpretation of Remotely Sensed Images
* 1992: Building a Model of a Road Junction Using Moving Vehicle Information
* 1993: Shape in Machine Vision
* 1993: Special issue: British Machine Vision Conference 1992
* 1994: 3-D Shape Recovery Using a Deformable Model
* 1994: Efficient Method for Contour Tracking Using Active Shape Models, An
* 1994: Efficient Method for Contour Tracking Using Active Shape Models, An
* 1994: Generating Spatiotemporal Models From Examples
* 1994: Learning Flexible Models from Image Sequences
* 1994: Shape Models from Image Sequences
* 1994: Using Shape and Intensity to Track Non-Rigid Objects
* 1995: 3-D Shape Recovery Using a Deformable Model
* 1995: Adaptive Eigenshape Model, An
* 1995: Automated Pivot Location for the Cartesian-Polar Hybrid Point Distribution Model
* 1995: Extending the Point Distribution Model Using Polar Coordinates
* 1995: Generating Spatiotemporal Models From Examples
* 1995: Generic 3-D shape model: Acquisitions and applications
* 1995: Learning the Distribution of Object Trajectories for Event Recognition
* 1996: Extending the Point Distribution Model Using Polar Coordinates
* 1996: Generating Spatiotemporal Models From Examples
* 1996: Generation of Semantic Regions from Image Sequences
* 1996: Global Alignment of MR Images Using a Scale Based Hierarchical Model
* 1996: Knowledge Intensive Image Interpretation: Introduction
* 1996: Learning the Distribution of Object Trajectories for Event Recognition
* 1996: Neural Networks in Human Motion Tracking: An Experimental Study
* 1996: Towards 3D hand tracking using a deformable model
* 1997: Improving Specificity in PDMs using a Hierarchical Approach
* 1997: Integrated Traffic and Pedestrian Model-Based Vision System, An
* 1997: Learning Deformable Models for Tracking the Human Body
* 1997: Neural Networks in Human Motion Tracking: An Experimental Study
* 1998: Acquisition and Use of Interaction Behaviour Models, The
* 1998: Building Qualitative Event Models Automatically from Visual Input
* 1998: Statistical Models of Object Interaction
* 1998: Wormholes in Shape Space: Tracking Through Discontinuous Changes in Shape
* 1999: Automated reconstruction of 3D models from real environments
* 1999: Hybrid Approach to the Construction of Triangulated 3D Models of Building Interiors
* 1999: Learning Behaviour Models of Human Activities
* 1999: Learning Structured Behavior Models using Variable Length Markov Models
* 2000: Constructing qualitative event models automatically from video input
* 2000: Statistical Models of Object Interaction
* 2001: Learning Variable-Length Markov Models of Behavior
* 2001: Reactive Memories: An Interactive Talking-Head
* 2002: Representation and synthesis of behaviour using Gaussian mixtures
* 2003: Cognitive Vision: Integrating Symbolic Qualitative Representations with Computer Vision
* 2003: Reactive Memories: An Interactive Talking-Head
* 2004: Detecting inexplicable behaviour
* 2005: On the feasibility of using a cognitive model to filter surveillance data
* 2007: Associating People Dropping off and Picking up Objects
* 2008: Comparative Study on Using Zernike Velocity Moments and Hidden Markov Models for Hand Gesture Recognition, A
* 2008: Detecting Carried Objects in Short Video Sequences
* 2008: Enhanced tracking and recognition of moving objects by reasoning about spatio-temporal continuity
* 2008: Motion segmentation by consensus
* 2009: Attribute Multiset Grammars for Global Explanations of Activities
* 2009: Recognizing linked events: Searching the space of feasible explanations
* 2010: Segmentation using Deformable Spatial Priors with Application to Clothing
* 2011: Temporal Structure Models for Event Recognition
* 2011: Who knows who: Inverting the Social Force Model for finding groups
* 2012: Building semantic scene models from unconstrained video
* 2012: Detecting Carried Objects from Sequences of Walking Pedestrians
* 2012: Egocentric Activity Monitoring and Recovery
* 2012: Explaining Activities as Consistent Groups of Events: A Bayesian Framework Using Attribute Multiset Grammars
* 2012: Special Editors' Introduction to the Special Issue on Award-Winning Papers from the IEEE Conference on Computer Vision and Pattern Recognition 2010 (CVPR 2010)
* 2012: Workflow Activity Monitoring Using Dynamics of Pair-Wise Qualitative Spatial Relations
* 2013: Automated Ground-Plane Estimation for Trajectory Rectification
* 2014: Context Aware Detection and Tracking
* 2014: Efficient Non-iterative Domain Adaptation of Pedestrian Detectors to Video Scenes
* 2014: Qualitative and Quantitative Spatio-temporal Relations in Daily Living Activity Recognition
* 2014: Real-time Activity Recognition by Discerning Qualitative Relationships Between Randomly Chosen Visual Features
* 2014: Unsupervised Detector Adaptation by Joint Dataset Feature Learning
* 2014: Weakly supervised pedestrian detector training by unsupervised prior learning and cue fusion in videos
* 2015: Joint Tracking and Event Analysis for Carried Object Detection
* 2018: Learning Hierarchical Models of Complex Daily Activities from Annotated Videos
* 2019: Unsupervised human activity analysis for intelligent mobile robots
* 2022: Epistemic Uncertainty-Weighted Loss for Visual Bias Mitigation
* 2023: 3D Shape Reconstruction of Semi-Transparent Worms
Includes: Hogg, D.C. Hogg, D.C.[David C.] Hogg, D.C.[David C]
77 for Hogg, D.C.
Hogg, D.W.
* 2016: Fast Direct Methods for Gaussian Processes
Hogg, M.[Michelle]
* 2020: Decoding Complex Erosion Responses for the Mitigation of Coastal Rockfall Hazards Using Repeat Terrestrial LiDAR
Hogg, P.[Peter]
* 2019: Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images
Hogg, R.E.
* 2014: Counterphase modulation flicker photometry: Phenotypic and genotypic associations
* 2014: Individual differences provide psychophysical evidence for separate on- and off-pathways deriving from short-wave cones
Includes: Hogg, R.E. Hogg, R.E.[Ruth E.]
Hogg, T.[Trevor]
* 1998: improved synergetic algorithm for image classification, An
* 1999: Explicit inversion: an approach to image analysis
* 1999: Learning in a self-organising pattern formation system
Hoggar, S.[Stuart]
* 2006: Mathematics of Digital Images