Denman, H.
* 2002: Content-Based Analysis for Video from Snooker Broadcasts
* 2003: Content-Based Analysis for Video from Snooker Broadcasts
* 2004: Gradient based dominant motion estimation with integral projections for real time video stabilisation
* 2012: Measuring noise correlation for improved video denoising
* 2015: Multipass encoding for reducing pulsing artifacts in cloud based video transcoding
Includes: Denman, H. Denman, H.[Hugh]
Denman, J.
* 2012: Two-Phase Method of Detecting Abnormalities in Aircraft Flight Data and Ranking Their Impact on Individual Flights, A
Denman, S.[Simon]
* 2006: Multi-Class Tracker Using a Scalable Condensation Filter, A
* 2006: Multi-view Intelligent Vehicle Surveillance System
* 2007: adaptive optical flow technique for person tracking systems, An
* 2009: Crowd Counting Using Multiple Local Features
* 2009: Dynamic Performance Measures for Object Tracking Systems
* 2009: Improved Simultaneous Computation of Motion Detection and Optical Flow for Object Tracking
* 2009: Soft-Biometrics: Unconstrained Authentication in a Surveillance Environment
* 2010: Accurate Silhouettes for Surveillance: Improved Motion Segmentation Using Graph Cuts
* 2010: Crowd Counting Using Group Tracking and Local Features
* 2010: Focus-score weighted super-resolution for uncooperative iris recognition at a distance and on the move
* 2010: Group Segmentation During Object Tracking Using Optical Flow Discontinuities
* 2010: Multi-Modal Object Tracking using Dynamic Performance Metrics
* 2011: 3D ellipsoid fitting for multi-view gait recognition
* 2011: Activity Modelling in Crowded Environments: A Soft-Decision Approach
* 2011: Determining operational measures from multi-camera surveillance systems using soft biometrics
* 2011: Evaluating Automatic Road Detection across a Large Aerial Imagery Collection
* 2011: Exploration of Feature Detector Performance in the Thermal-Infrared Modality, An
* 2011: Feature-domain super-resolution for iris recognition
* 2011: Scene Invariant Crowd Counting
* 2011: Textures of optical flow for real-time anomaly detection in crowds
* 2011: Unusual Event Detection in Crowded Scenes Using Bag of LBPs in Spatio-Temporal Patches
* 2012: Activity Analysis in Complicated Scenes Using DFT Coefficients of Particle Trajectories
* 2012: Anomalous Event Detection Using a Semi-Two Dimensional Hidden Markov Model
* 2012: Backfilled GEI: A Cross-Capture Modality Gait Feature for Frontal and Side-View Gait Recognition, The
* 2012: Can You Describe Him for Me? A Technique for Semantic Person Search in Video
* 2012: Database for Person Re-Identification in Multi-Camera Surveillance Networks, A
* 2012: Feature-domain super-resolution framework for Gabor-based face and iris recognition
* 2012: Spatio Temporal Feature Evaluation for Action Recognition
* 2012: Unusual Scene Detection Using Distributed Behaviour Model and Sparse Representation
* 2013: Evaluation of Different Features and Learning Models for Anomalous Event Detection, An
* 2013: Histogram of Weighted Local Directions for Gait Recognition
* 2013: Quality Based Frame Selection for Face Clustering in News Video
* 2013: Recognising Team Activities from Noisy Data
* 2013: Semi-Binary Based Video Features for Activity Representation
* 2014: Automatic UAV Forced Landing Site Detection Using Machine Learning
* 2014: Local inter-session variability modelling for object classification
* 2014: Locating People in Video from Semantic Descriptions: A New Database and Approach
* 2014: MRF based abnormal event detection approach using motion and appearance features, An
* 2014: Multiple Instance Dictionary Learning for Activity Representation
* 2014: Real-time video event detection in crowded scenes using MPEG derived features: A multiple instance learning approach
* 2014: Scene invariant multi camera crowd counting
* 2014: Supervised Latent Dirichlet Allocation Models for Efficient Activity Representation
* 2015: Class-specific sparse codes for representing activities
* 2015: Closed-Form Solutions for Low-Rank Non-Rigid Reconstruction
* 2015: Efficient and Robust System for Multiperson Event Detection in Real-World Indoor Surveillance Scenes, An
* 2015: evaluation of crowd counting methods, features and regression models, An
* 2015: Large scale monitoring of crowds and building utilisation: A new database and distributed approach
* 2015: Learning Temporal Alignment Uncertainty for Efficient Event Detection
* 2015: Robust Automatic Face Clustering in News Video
* 2015: Score-Level Multibiometric Fusion Based on Dempster-Shafer Theory Incorporating Uncertainty Factors
* 2015: Searching for people using semantic soft biometric descriptions
* 2016: Complex Event Detection Using Joint Max Margin and Semantic Features
* 2016: Discovery of facial motions using deep machine perception
* 2016: robust UAV landing site detection system using mid-level discriminative patches, A
* 2016: Vertical Axis Detection for Sport Video Analytics
* 2017: Deep discovery of facial motions using a shallow embedding layer
* 2017: From Affine Rank Minimization Solution to Sparse Modeling
* 2017: Going Deeper: Autonomous Steering with Neural Memory Networks
* 2017: Single image depth prediction using super-column super-pixel features
* 2017: Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition
* 2017: Using Synthetic Data to Improve Facial Expression Analysis with 3D Convolutional Networks
* 2018: Deep Decision Trees for Discriminative Dictionary Learning with Adversarial Multi-agent Trajectories
* 2018: Deep Four-Stream Siamese Convolutional Neural Network with Joint Verification and Identification Loss for Person Re-Detection, A
* 2018: GD-GAN: Generative Adversarial Networks for Trajectory Prediction and Group Detection in Crowds
* 2018: Multi-level Sequence GAN for Group Activity Recognition
* 2018: Rethinking Planar Homography Estimation Using Perspective Fields
* 2018: Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks
* 2018: Tracking by Prediction: A Deep Generative Model for Mutli-person Localisation and Tracking
* 2019: Coupled Generative Adversarial Network for Continuous Fine-Grained Action Segmentation
* 2019: Multimodal clothing recognition for semantic search in unconstrained surveillance imagery
* 2019: Neighbourhood Context Embeddings in Deep Inverse Reinforcement Learning for Predicting Pedestrian Motion Over Long Time Horizons
* 2019: Predicting the Future: A Jointly Learnt Model for Action Anticipation
* 2019: Scene Invariant Virtual Gates Using DNNs
* 2020: Fine-grained action segmentation using the semi-supervised action GAN
* 2020: Fruit Detection in the Wild: the Impact of Varying Conditions and Cultivar
* 2020: Hierarchical Attention Network for Action Segmentation
* 2020: Joint identification-verification for person re-identification: A four stream deep learning approach with improved quartet loss function
* 2020: LSTM guided ensemble correlation filter tracking with appearance model pool
* 2020: MTRNet++: One-stage mask-based scene text eraser
* 2020: Semantic Consistency and Identity Mapping Multi-Component Generative Adversarial Network for Person Re-Identification
* 2020: Sparse Convolutions on Continuous Domains for Point Cloud and Event Stream Networks
* 2021: Deep Inverse Reinforcement Learning for Behavior Prediction in Autonomous Driving: Accurate Forecasts of Vehicle Motion
* 2021: IGSSTRCF: Importance Guided Sparse Spatio-Temporal Regularized Correlation Filters For Tracking
* 2021: Learning Regional Attention Over Multi-Resolution Deep Convolutional Features for Trademark Retrieval
* 2021: TMMF: Temporal Multi-Modal Fusion for Single-Stage Continuous Gesture Recognition
* 2022: Automated Detection of Koalas with Deep Learning Ensembles
* 2022: Channel Graph Regularized Correlation Filters for Visual Object Tracking
* 2022: efficient framework for zero-shot sketch-based image retrieval, An
* 2022: Learning test-time augmentation for content-based image retrieval
* 2022: SESS: Saliency Enhancing with Scaling and Sliding
* 2022: Split n merge net: A dynamic masking network for multi-task attention
* 2023: Continuous Human Action Recognition for Human-Machine Interaction: A Review
* 2023: Multi-stage stacked temporal convolution neural networks (MS-S-TCNs) for biosignal segmentation and anomaly localization
* 2023: Pose-driven attention-guided image generation for person re-Identification
Includes: Denman, S.[Simon] Denman, S.
94 for Denman, S.
Denmon, S.
* 2011: Compressive Sensing for Gait Recognition