Darra, N.[Nicoleta]
* 2022: Development of a Multi-Scale Tomato Yield Prediction Model in Azerbaijan Using Spectral Indices from Sentinel-2 Imagery
Darras, K.
* 2016: Automatic Segmentation of Wrist Bones in CT Using a Statistical Wrist Shape+Pose Model
Darrell, T.J.[Trevor J.]
* 1988: Pyramid Based Depth from Focus
* 1989: Simple, Real-Time Range Camera, A
* 1990: Depth from Focus Using a Pyramid Architecture
* 1990: Segmentation by Minimal Description
* 1991: Cooperative Robust Estimation Using Layers of Support
* 1991: On the representation of occluded shapes
* 1991: Robust Estimation of a Multi-Layered Motion Representation
* 1992: On the Use of Nulling Filters to Separate Transparent Motions
* 1992: Space-Time Gestures
* 1993: Nulling Filters and the Separation of Transparent Motions
* 1993: Separation of Transparent Motion into Layers Using Velocity-Tuned Mechanisms
* 1993: Space-Time Gestures
* 1994: Robust Estimation of Multiple Models in the Structure from Motion Domain
* 1994: Simple Range Cameras Based on Focal Error
* 1994: Tracking Facial Motion
* 1995: Cooperative Robust Estimation Using Layers of Support
* 1995: Pfinder: Real-Time Tracking of the Human Body
* 1996: Active Face Tracking and Pose Estimation in an Interactive Room
* 1996: Active Gesture Recognition Using Partially Observable Markov Decision Processes
* 1996: Pfinder: Real-Time Tracking of the Human Body
* 1996: Task-Specific Gesture Analysis in Real-Time Using Interpolated Views
* 1997: Alive System: Wireless, Full-Body Interaction with Autonomous Agents, The
* 1997: Perceptive Spaces for Performance and Entertainment: Untethered Interaction Using Computer Vision and Audition
* 1997: Pfinder: Real-Time Tracking of the Human Body
* 1998: Integrated Person Tracking Using Stereo, Color, and Pattern Detection
* 1998: Magic Morphin' Mirror: Person Detection and Tracking
* 1998: Radial Cumulative Similarity Transform for Robust Image Correspondence, A
* 1998: Robust, Real-Time People Tracking in Open Environments Using Integrated Stereo, Color, and Face Detection
* 1998: Virtual Mirror Interface Using Real-Time Robust Face Tracking, A
* 1999: 3D Pose Tracking with Linear Depth and Brightness Constraints
* 1999: Background Estimation and Removal Based on Range and Color
* 1999: Dynamic Occluding Contours: A New External-energy Term for Snakes
* 1999: Rendering Articulated Figures from Examples
* 2000: Articulated-Pose Estimation using Brightness and Depth-Constancy Constraints
* 2000: Integrated Person Tracking Using Stereo, Color, and Pattern Detection
* 2001: Correspondence with Cumulative Similarity Transforms
* 2001: Integrated Face and Gait Recognition from Multiple Views
* 2001: Method and apparatus for personnel detection and tracking
* 2001: Motion Estimation from Disparity Images
* 2001: Motion Estimation from Disparity Images
* 2001: Plan-View Trajectory Estimation with Dense Stereo Background Models
* 2001: Plan-View Trajectory Estimation with Dense Stereo Background Models
* 2001: Range Segmentation Using Visibility Constraints
* 2001: Range Segmentation Using Visibility Constraints
* 2001: Range-based Foreground Detection Using Visibility Constraints
* 2001: Reducing Drift in Parametric Motion Tracking
* 2001: Reducing Drift in Parametric Motion Tracking
* 2001: Using Multiple-Hypothesis Disparity Maps and Image Velocity for 3-D Motion Estimation
* 2002: Activity maps for location-aware computing
* 2002: Exploring Vision-Based Interfaces: How to Use Your Head in Dual Pointing Tasks
* 2002: Face Recognition from Long-Term Observations
* 2002: Fast 3D model acquisition from stereo images
* 2002: Fast stereo-based head tracking for interactive environments
* 2002: Method and apparatus for personnel detection and tracking
* 2002: On probabilistic combination of face and gait cues for identification
* 2002: Probabalistic Models and Informative Subspaces for Audiovisual Correspondence
* 2002: Range Segmentation Using Visibility Constraints
* 2002: Stereo tracking using ICP and normal flow constraint
* 2002: Using Multiple-Hypothesis Disparity Maps and Image Velocity for 3-D Motion Estimation
* 2003: Adaptive view-based appearance models
* 2003: Background estimation and segmentation based on range and color
* 2003: Bayesian approach to image-based visual hull reconstruction, A
* 2003: Constraining human body tracking
* 2003: Fast Contour Matching Using Approximate Earth Mover's Distance
* 2003: Fast Pose Estimation with Parameter-Sensitive Hashing
* 2003: Fast Pose Estimation with Parameter-Sensitive Hashing
* 2003: Inferring 3D Structure with a Statistical Image-Based Shape Model
* 2003: Inferring 3D Structure with a Statistical Image-Based Shape Model
* 2003: Light Field Morphable Models
* 2003: Pose Estimation Using 3D View-Based Eigenspaces
* 2004: Combining Simple Models to Approximate Complex Dynamics
* 2004: Efficient Image Matching with Distributions of Local Invariant Features
* 2004: Fast Contour Matching Using Approximate Earth Mover's Distance
* 2004: Searching the web with mobile images for location recognition
* 2004: Simultaneous calibration and tracking with a network of non-overlapping sensors
* 2004: Virtual Visual Hulls: Example-Based 3D Shape Estimation from a Single Silhouette
* 2004: Virtual Visual Hulls: Example-Based 3D Shape Inference from Silhouettes
* 2005: Avoiding the Streetlight Effect: Tracking by Exploring Likelihood Modes
* 2005: Combining Object and Feature Dynamics in Probabilistic Tracking
* 2005: Combining Object and Feature Dynamics in Probabilistic Tracking
* 2005: Efficient Image Matching with Distributions of Local Invariant Features
* 2005: Face Recognition with Image Sets Using Manifold Density Divergence
* 2005: Incorporating Object Tracking Feedback into Background Maintenance Framework
* 2005: Learning Appearance Manifolds from Video
* 2005: Nonlinear Latent Variable Models for Video Sequences
* 2005: On Modelling Nonlinear Shape-and-Texture Appearance Manifolds
* 2005: Pyramid Match Kernel: Discriminative Classification with Sets of Image Features, The
* 2005: Pyramid Match Kernel: Discriminative Classification with Sets of Image Features, The
* 2005: Visual Speech Recognition with Loosely Synchronized Feature Streams
* 2006: Approximate Correspondences in High Dimensions
* 2006: Conditional Random People: Tracking Humans with CRFs and Grid Filters
* 2006: Non-parametric and light-field deformable models
* 2006: Pyramid Match Kernel: Discriminative Classification with Sets of Image Features, The
* 2006: Unsupervised Learning of Categories from Sets of Partially Matching Image Features
* 2007: Active Learning with Gaussian Processes for Object Categorization
* 2007: Adaptive Vocabulary Forests for Dynamic Indexing and Category Learning
* 2007: Combining Object and Feature Dynamics in Probabilistic Tracking
* 2007: Head gestures for perceptual interfaces: The role of context in improving recognition
* 2007: Hidden Conditional Random Fields
* 2007: Latent-Dynamic Discriminative Models for Continuous Gesture Recognition
* 2007: Learning to Transform Time Series with a Few Examples
* 2007: Learning Visual Representations using Images with Captions
* 2007: Pyramid Match Hashing: Sub-Linear Time Indexing Over Partial Correspondences
* 2008: Autotagging Facebook: Social network context improves photo annotation
* 2008: Dynamic visual category learning
* 2008: Fast concurrent object classification and localization
* 2008: Rank Priors for Continuous Non-Linear Dimensionality Reduction
* 2008: Reducing drift in differential tracking
* 2008: Scalable classifiers for Internet vision tasks
* 2008: Sparse probabilistic regression for activity-independent human pose inference
* 2008: Transfer learning for image classification with sparse prototype representations
* 2008: Transfer learning for image classification with sparse prototype representations
* 2008: Transferring Nonlinear Representations using Gaussian Processes with a Shared Latent Space
* 2008: Unsupervised feature selection via distributed coding for multi-view object recognition
* 2009: Co-training with noisy perceptual observations
* 2009: Fast concurrent object localization and recognition
* 2009: Multistream Articulatory Feature-Based Models for Visual Speech Recognition
* 2009: Rank Priors for Continuous Non-Linear Dimensionality Reduction
* 2010: Adapting Visual Category Models to New Domains
* 2010: Gaussian Processes for Object Categorization
* 2010: Learning to Recognize Objects from Unseen Modalities
* 2010: Toward Large-Scale Face Recognition Using Social Network Context
* 2011: Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance
* 2011: category-level 3-D object dataset: Putting the Kinect to work, A
* 2011: Finding lost children
* 2011: Learning cross-modality similarity for multinomial data
* 2011: Learning object color models from multi-view constraints
* 2011: NBNN kernel, The
* 2011: probabilistic model for recursive factorized image features, A
* 2011: Supervised hierarchical Pitman-Yor process for natural scene segmentation
* 2011: Visual grasp affordances from appearance-based cues
* 2011: What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
* 2012: Beyond spatial pyramids: Receptive field learning for pooled image features
* 2012: Discovering Latent Domains for Multisource Domain Adaptation
* 2012: From pixels to physics: Probabilistic color de-rendering
* 2012: Pose pooling kernels for sub-category recognition
* 2012: Sparselet Models for Efficient Multiclass Object Detection
* 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)
* 2013: Deformable Part Descriptors for Fine-Grained Recognition and Attribute Prediction
* 2013: Latent Task Adaptation with Large-Scale Hierarchies
* 2013: Semi-supervised Domain Adaptation with Instance Constraints
* 2013: YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-Shot Recognition
* 2014: Anytime Recognition of Objects and Scenes
* 2014: Continuous Manifold Based Adaptation for Evolving Visual Domains
* 2014: Exemplar-Specific Patch Features for Fine-Grained Recognition
* 2014: Guest Editor's Introduction to the Special Issue on Domain Adaptation for Vision Applications
* 2014: Learning Scalable Discriminative Dictionary with Sample Relatedness
* 2014: Modeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images
* 2014: PANDA: Pose Aligned Networks for Deep Attribute Modeling
* 2014: Part-Based R-CNNs for Fine-Grained Category Detection
* 2014: Recognizing Image Style
* 2014: Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
* 2015: Constrained Convolutional Neural Networks for Weakly Supervised Segmentation
* 2015: Deformable part models are convolutional neural networks
* 2015: Detector discovery in the wild: Joint multiple instance and representation learning
* 2015: Fully Convolutional Networks for Semantic Segmentation
* 2015: Generalized Sparselet Models for Real-Time Multiclass Object Recognition
* 2015: Introduction to the CVIU special issue on 'Parts and Attributes: Mid-level representation for object recognition, scene classification and object detection'
* 2015: Learning the Structure of Deep Convolutional Networks
* 2015: Long-Term Recurrent Convolutional Networks for Visual Recognition and Description
* 2015: Scene Intrinsics and Depth from a Single Image
* 2015: Sequence to Sequence -- Video to Text
* 2015: Simultaneous Deep Transfer Across Domains and Tasks
* 2015: Spatial Semantic Regularisation for Large Scale Object Detection
* 2016: Best Practices for Fine-Tuning Visual Classifiers to New Domains
* 2016: Clockwork Convnets for Video Semantic Segmentation
* 2016: Compact Bilinear Pooling
* 2016: Context Encoders: Feature Learning by Inpainting
* 2016: Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data
* 2016: Generating Visual Explanations
* 2016: Grounding of Textual Phrases in Images by Reconstruction
* 2016: Learning with Side Information through Modality Hallucination
* 2016: Natural Language Object Retrieval
* 2016: Neural Module Networks
* 2016: Region-Based Convolutional Networks for Accurate Object Detection and Segmentation
* 2016: Segmentation from Natural Language Expressions
* 2017: Adversarial Discriminative Domain Adaptation
* 2017: Captioning Images with Diverse Objects
* 2017: Curiosity-Driven Exploration by Self-Supervised Prediction
* 2017: End-to-End Learning of Driving Models from Large-Scale Video Datasets
* 2017: Fully Convolutional Networks for Semantic Segmentation
* 2017: Generalized Orderless Pooling Performs Implicit Salient Matching
* 2017: Learning Detection with Diverse Proposals
* 2017: Learning Features by Watching Objects Move
* 2017: Learning to Reason: End-to-End Module Networks for Visual Question Answering
* 2017: Localizing Moments in Video with Natural Language
* 2017: Long-Term Recurrent Convolutional Networks for Visual Recognition and Description
* 2017: Modeling Relationships in Referential Expressions with Compositional Modular Networks
* 2018: Deep Layer Aggregation
* 2018: Explainable Neural Computation via Stack Neural Module Networks
* 2018: Fooling Vision and Language Models Despite Localization and Attention Mechanism
* 2018: Grounding Visual Explanations
* 2018: Guest Editors' Introduction to the Special Section on Learning with Shared Information for Computer Vision and Multimedia Analysis
* 2018: Learning Instance Segmentation by Interaction
* 2018: Learning to Segment Every Thing
* 2018: Multi-content GAN for Few-Shot Font Style Transfer
* 2018: Multimodal Explanations: Justifying Decisions and Pointing to the Evidence
* 2018: SkipNet: Learning Dynamic Routing in Convolutional Networks
* 2018: Textual Explanations for Self-Driving Vehicles
* 2018: Women Also Snowboard: Overcoming Bias in Captioning Models
* 2018: Zero-Shot Visual Imitation
* 2019: Adversarial Inference for Multi-Sentence Video Description
* 2019: Disentangling Propagation and Generation for Video Prediction
* 2019: Few-Shot Object Detection via Feature Reweighting
* 2019: Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
* 2019: Hierarchical Discrete Distribution Decomposition for Match Density Estimation
* 2019: Joint Monocular 3D Vehicle Detection and Tracking
* 2019: Language-Conditioned Graph Networks for Relational Reasoning
* 2019: Robust Change Captioning
* 2019: Semi-Supervised Domain Adaptation via Minimax Entropy
* 2019: Spatio-Temporal Action Graph Networks
* 2019: TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning
* 2019: Variational Adversarial Active Learning
* 2020: Advisable Learning for Self-Driving Vehicles by Internalizing Observation-to-Action Rules
* 2020: BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
* 2020: Compositional GAN: Learning Image-Conditional Binary Composition
* 2020: Hierarchical Style-based Networks for Motion Synthesis
* 2020: Identity-Aware Multi-Sentence Video Description
* 2020: Iterative Answer Prediction With Pointer-Augmented Multimodal Transformers for TextVQA
* 2020: Learning Canonical Representations for Scene Graph to Image Generation
* 2020: Learning Saliency Propagation for Semi-Supervised Instance Segmentation
* 2020: Seeing the Un-scene: Learning Amodal Semantic Maps for Room Navigation
* 2020: Something-Else: Compositional Action Recognition With Spatial-Temporal Interaction Networks
* 2020: Weakly-supervised Action Localization with Expectation-maximization Multi-instance Learning
* 2020: Whole Is More Than Its Parts? From Explicit to Implicit Pose Normalization, The
* 2021: Body2Hands: Learning to Infer 3D Hands from Conversational Gesture Body Dynamics
* 2021: Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation
* 2021: Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning
* 2021: Predicting with Confidence on Unseen Distributions
* 2021: Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation
* 2021: Quasi-Dense Similarity Learning for Multiple Object Tracking
* 2021: Region Similarity Representation Learning
* 2021: Rethinking preventing class-collapsing in metric learning with margin-based losses
* 2021: Robust Object Detection via Instance-Level Temporal Cycle Confusion
* 2021: SelfAugment: Automatic Augmentation Policies for Self-Supervised Learning
* 2021: Temporal Action Detection with Multi-level Supervision
* 2021: Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density
* 2022: Contrastive Test-Time Adaptation
* 2022: ConvNet for the 2020s, A
* 2022: DETReg: Unsupervised Pretraining with Region Priors for Object Detection
* 2022: Learning to Detect Every Thing in an Open World
* 2022: Learning to Listen: Modeling Non-Deterministic Dyadic Facial Motion
* 2022: Object-Region Video Transformers
* 2022: On Guiding Visual Attention with Language Specification
* 2022: Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly
* 2022: Self-Supervised Pretraining Improves Self-Supervised Pretraining
* 2022: Strumming to the Beat: Audio-Conditioned Contrastive Video Textures
* 2022: Studying Bias in GANs Through the Lens of Race
* 2022: TL;DW? Summarizing Instructional Videos with Task Relevance and Cross-Modal Saliency
* 2023: Back to the Source: Diffusion-Driven Adaptation to Test-Time Corruption
* 2023: Can Language Models Learn to Listen?
* 2023: Exploring Simple and Transferable Recognition-Aware Image Processing
* 2023: Monocular Quasi-Dense 3D Object Tracking
* 2023: More Control for Free! Image Synthesis with Semantic Diffusion Guidance
* 2023: QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Tracking
* 2023: Revisiting Generalizability in Deepfake Detection: Improving Metrics and Stabilizing Transfer
* 2023: Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
* 2023: Top-Down Visual Attention from Analysis by Synthesis
* 2023: Watch Those Words: Video Falsification Detection Using Word-Conditioned Facial Motion
* 2024: Multitask Vision-Language Prompt Tuning
* 2024: Proceedings of the Workshop on 3D Geometry Generation for Scientific Computing
* 2024: PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data
* 2024: Shape-Guided Diffusion with Inside-Outside Attention
* 2024: Simple Token-Level Confidence Improves Caption Correctness
Includes: Darrell, T.J.[Trevor J.] Darrell, T.J. Darrell, T.J.[Trever J.]
264 for Darrell, T.J.
Darrodi, M.M.[Maryam Mohammadzadeh]
* 2015: Reference data set for camera spectral sensitivity estimation
* 2016: Rank-based camera spectral sensitivity estimation
Darrozes, J.[Jose]
* 2018: Investigation of Short-Term Evolution of Soil Characteristics over the Lake Chad Basin Using GRACE Data
* 2018: Multi-Satellite Altimeter Validation along the French Atlantic Coast in the Southern Bay of Biscay from ERS-2 to SARAL
* 2019: Identifying 2010 Xynthia Storm Signature in GNSS-R-Based Tide Records
* 2020: Recovery of Rapid Water Mass Changes (RWMC) by Kalman Filtering of GRACE Observations
* 2021: Automatic Detection of Inland Water Bodies along Altimetry Tracks for Estimating Surface Water Storage Variations in the Congo Basin
* 2021: Innovative Slepian Approach to Invert GRACE KBRR for Localized Hydrological Information at the Sub-Basin Scale, An
* 2021: Robust Kalman Filter Soil Moisture Inversion Model Using GPS SNR Data: A Dual-Band Data Fusion Approach
* 2022: Innovative Slepian Approach to Invert GRACE KBRR for Localized Hydrological Information at the Sub-Basin Scale, An
* 2022: Regional Seafloor Topography by Extended Kalman Filtering of Marine Gravity Data without Ship-Track Information
Includes: Darrozes, J.[Jose] Darrozes, J.[José]
9 for Darrozes, J.