Fleed, D.J.[David J.]
* 2023: Generalist Framework for Panoptic Segmentation of Images and Videos, A
Fleet, D.[David]
* 2016: Guest Editorial: Human Activity Understanding from 2D and 3D Data
Fleet, D.J.
* 1984: Cascaded Filter Approach to the Construction of Velocity Selective Mechanisms, A
* 1984: Early Processing of Spatio-Temporal Visual Information, The
* 1984: Motion Understanding Meets Early Vision: An Introduction
* 1984: Spatio-Temporal Model for Early Visual Processing, A
* 1985: Hierarchial Construction of Orientation and Velocity Selective Filters
* 1985: Spatiotemporal Inseparability in Early Visual Processing
* 1985: Velocity Extraction without Form Interpretation
* 1988: Towards a Theory of Motion Understanding in Man and Machine
* 1989: Computation of Normal Velocity from Local Phase Information
* 1989: Computation of Normal Velocity from Local Phase Information
* 1989: Hierarchial Construction of Orientation and Velocity Selective Filters
* 1989: Phase-Based Disparity Measurement
* 1990: Computation of Component Image Velocity from Local Phase Information
* 1990: Scale-Space Singularities
* 1991: Phase Singularities in Scale-Space
* 1991: Phase-Based Disparity Measurement
* 1991: Stability of Phase Information
* 1992: Measurement of Image Velocity
* 1992: Multiple Motions from Instantaneous Frequency
* 1992: On Transparent Motion Computation
* 1992: Performance of Optical Flow Techniques
* 1993: Stability of Phase Information
* 1994: Computational analysis of non-Fourier motion
* 1994: Performance of Optical Flow Techniques
* 1994: Stable estimation of image orientation
* 1995: Recursive Filters For Optical-Flow
* 1996: Neural encoding of binocular disparity: Energy model, position shifts and phase shifts
* 1997: Embedding Invisible Information in Color Images
* 1997: Learning Parameterized Models of Image Motion
* 1998: Framework for Modeling Appearance Change in Image Sequences, A
* 1998: Linear and nonlinear transparency in binocular vision
* 1998: Motion Feature Detection Using Steerable Flow Fields
* 1998: Second-order motions contribute to vection
* 1999: Probabilistic Detection and Tracking of Motion Discontinuities
* 1999: Stereopsis from Contrast Envelopes
* 2000: Computing Optical Flow with Physical Models of Brightness Variation
* 2000: Design and Use of Linear Models for Image Motion Analysis
* 2000: Disparity Tuning as Simulated by a Neural Net
* 2000: Likelihood Functions and Confidence Bounds for Total-Least-Squares Problems
* 2000: Probabilistic Detection and Tracking of Motion Boundaries
* 2000: Robustly Estimating Changes in Image Appearance
* 2000: Stochastic Tracking of 3D Human Figures using 2D Image Motion
* 2001: Computing Optical Flow with Physical Models of Brightness Variation
* 2001: People Tracking Using Hybrid Monte Carlo Filtering
* 2001: Probabilistic Tracking of Motion Boundaries with Spatiotemporal Predictions
* 2001: Robust Online Appearance Models for Visual Tracking
* 2001: Texture space
* 2002: Bayesian Inference of Visual Motion Boundaries
* 2002: Hybrid Monte Carlo filtering: Edge-based people tracking
* 2002: Layered Motion Representation with Occlusion and Compact Spatial Support, A
* 2002: Probabilistic Theory of Occupancy and Emptiness, A
* 2003: Error-in-variables likelihood functions for motion estimation
* 2003: Robust Online Appearance Models for Visual Tracking
* 2005: Monocular 3-D Tracking of the Golf Swing
* 2005: Monocular 3-D Tracking of the Golf Swing
* 2005: Priors for People Tracking from Small Training Sets
* 2006: 3D People Tracking with Gaussian Process Dynamical Models
* 2006: Temporal motion models for monocular and multiview 3D human body tracking
* 2007: Higher-order Autoregressive Models for Dynamic Textures
* 2007: Modeling Human Locomotion with Topologically Constrained Latent Variable Models
* 2007: Physics-Based Person Tracking Using Simplified Lower-Body Dynamics
* 2007: Special issue on spatial coherence for visual motion analysis
* 2008: From skeletons to bone graphs: Medial abstraction for object recognition
* 2008: Gaussian Process Dynamical Models for Human Motion
* 2008: Gaussian Process Dynamical Models for Human Motion
* 2008: Kneed Walker for human pose tracking, The
* 2008: Model-based hand tracking with texture, shading and self-occlusions
* 2009: Backing Off: Hierarchical Decomposition of Activity for 3d Novel Pose Recovery
* 2009: Estimating Contact Dynamics
* 2009: Shared Kernel Information Embedding for Discriminative Inference
* 2009: Stochastic Image Denoising
* 2009: TurboPixels: Fast Superpixels Using Geometric Flows
* 2010: Dynamical binary latent variable models for 3D human pose tracking
* 2010: Human attributes from 3D pose tracking
* 2010: Physics-Based Person Tracking Using the Anthropomorphic Walker
* 2011: Bone graphs: Medial shape parsing and abstraction
* 2011: Model-Based 3D Hand Pose Estimation from Monocular Video
* 2011: Object categorization using bone graphs
* 2012: Fast search in Hamming space with multi-index hashing
* 2012: Human attributes from 3D pose tracking
* 2012: Shared Kernel Information Embedding for Discriminative Inference
* 2013: Cartesian K-Means
* 2014: Fast Exact Search in Hamming Space With Multi-Index Hashing
* 2014: Posebits for Monocular Human Pose Estimation
* 2015: Building proteins in a day: Efficient 3D molecular reconstruction
* 2015: Efficient Optimization for Sparse Gaussian Process Regression
* 2017: Building Proteins in a Day: Efficient 3D Molecular Structure Estimation with Electron Cryomicroscopy
* 2018: Hierarchical Video Understanding
* 2018: Walking on Thin Air: Environment-Free Physics-Based Markerless Motion Capture
* 2022: Disentangling Architecture and Training for Optical Flow
* 2022: Kubric: A scalable dataset generator
* 2023: Image Super-Resolution via Iterative Refinement
* 2023: Imagen Editor and EditBench: Advancing and Evaluating Text-Guided Image Inpainting
* 2023: RobustNeRF: Ignoring Distractors with Robust Losses
Includes: Fleet, D.J. Fleet, D.J.[David J.] Fleet, D.J.[David J]
94 for Fleet, D.J.
Fleet, E.[Erin]
* 2017: Selecting an Optimized COTS Filter Set for Multispectral Plenoptic Sensing
Fleet, S.L.
* 2004: Classifying non-uniformly sampled vector-valued curves