Yuille, A.[Alan]
Co Author Listing * 3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation
* Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shape
* CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
* Diffusion Models as Masked Autoencoders
* InstMove: Instance Motion for Object-centric Video Segmentation
* Masked Autoencoders Enable Efficient Knowledge Distillers
* Multispectral Video Semantic Segmentation: A Benchmark Dataset and Baseline
* PoseExaminer: Automated Testing of Out-of-Distribution Robustness in Human Pose and Shape Estimation
* SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training
9 for Yuille, A.
Yuille, A.L.[Alan L.]
Co Author Listing * Home Page.
* email: Yuille, A.L.[Alan L.]: yuille AT stat ucla edu
* 3D Coarse-to-Fine Framework for Volumetric Medical Image Segmentation, A
* 3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training
* 3D Symmetry-Curvature Duality Theorems
* 5+/-2 Eigenimages Suffice: An Empirical Investigation of Low-Dimensional Lighting Models
* A* perspective on deterministic optimization for deformable templates, An
* A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation
* Active Mask Hierarchies for Object Detection
* Active Patch Model for Real World Texture and Appearance Classification, An
* Active Vision
* AdaBoost for Text Detection in Natural Scene
* Adaptive occlusion state estimation for human pose tracking under self-occlusions
* Adversarial Attacks Beyond the Image Space
* Adversarial Examples for Edge Detection: They Exist, and They Transfer
* Adversarial Examples for Semantic Segmentation and Object Detection
* Adversarial Examples Improve Image Recognition
* Alarm System for Segmentation Algorithm Based on Shape Model, An
* Algorithms from statistical physics for generative models of images
* Amodal Segmentation through Out-of-Task and Out-of-Distribution Generalization with a Bayesian Model
* Approach to Pose-Based Action Recognition, An
* Are Labels Necessary for Neural Architecture Search?
* Attention to Scale: Scale-Aware Semantic Image Segmentation
* Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
* Automated Extraction of the Cortical Sulci Based on a Supervised Learning Approach
* Axial-Deeplab: Stand-alone Axial-Attention for Panoptic Segmentation
* Bas-Relief Ambiguity, The
* bayesian network framework for relational shape matching, A
* BNET: Batch Normalization With Enhanced Linear Transformation
* Bottom-Up and Top-down Object Detection using Primal Sketch Features and Graphical Models
* Bottom-Up Segmentation for Top-Down Detection
* Boundary Detection Benchmarking: Beyond F-Measures
* C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation
* Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images
* CLEVR-Ref+: Diagnosing Visual Reasoning With Referring Expressions
* CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection
* Coarse-To-Fine Incremental Few-Shot Learning
* CoKe: Contrastive Learning for Robust Keypoint Detection
* Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion
* Common Framework for Image Segmentation, A
* compositional approach to learning part-based models of objects, A
* Compositional Convolutional Neural Networks: A Deep Architecture With Innate Robustness to Partial Occlusion
* Compositional Convolutional Neural Networks: A Robust and Interpretable Model for Object Recognition Under Occlusion
* Compositor: Bottom-Up Clustering and Compositing for Robust Part and Object Segmentation
* Computer vision needs a core and foundations
* Computing importance of 2D contour parts by reconstructability
* Context-Aware Group Captioning via Self-Attention and Contrastive Features
* Context-Enhanced Stereo Transformer
* CORL: Compositional Representation Learning for Few-Shot Classification
* CP 2: Copy-Paste Contrastive Pretraining for Semantic Segmentation
* CRAVES: Controlling Robotic Arm With a Vision-Based Economic System
* Creation of Structure in Dynamic Shape, The
* CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
* Data Fusion for Sensory Information Processing Systems
* Deep Co-Training for Semi-Supervised Image Recognition
* Deep Differentiable Random Forests for Age Estimation
* Deep Distance Transform for Tubular Structure Segmentation in CT Scans
* Deep Nets: What have They Ever Done for Vision?
* Deep Networks Under Scene-Level Supervision for Multi-Class Geospatial Object Detection from Remote Sensing Images
* Deep Regression Forests for Age Estimation
* DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection
* DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
* Deeply Shape-guided Cascade for Instance Segmentation
* DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images
* DeepVoting: A Robust and Explainable Deep Network for Semantic Part Detection Under Partial Occlusion
* Deformable Templates for Face Recognition
* Deformable templates for feature extraction from medical images
* Deformable Templates, Robust Statistics, and Hough Transforms
* Delving into Masked Autoencoders for Multi-Label Thorax Disease Classification
* Depth Recovery Algorithm Using Defocus Information, A
* Describing Surfaces
* Detect What You Can: Detecting and Representing Objects Using Holistic Models and Body Parts
* Detecting and reading text in natural scenes
* Detecting Object Boundaries Using Low-, Mid-, and High-level Information
* DetectoRS: Detecting Objects with Recursive Feature Pyramid and Switchable Atrous Convolution
* Determining Generative Models of Objects Under Varying Illumination: Shape and Albedo from Multiple Images Using SVD and Integrability
* Determining the Optimal Weights in Multiple Objective Function Optimization
* Direct Passive Navigation: Analytical Solution for Quadratic Patches
* DOC: Deep OCclusion Estimation from a Single Image
* Double-Loop Algorithm to Minimize the Bethe and Kikuchi Free Energies, A
* Double-Loop Algorithm to Minimize the Bethe Free Energy, A
* Editorial: Deep Learning for Computer Vision
* Efficient Deformable Template Detection and Localization without User Initialization
* Efficient Multilevel Brain Tumor Segmentation With Integrated Bayesian Model Classification
* Efficient Optimization of a Deformable Template Using Dynamic Programming
* Efficient variational inference in large-scale Bayesian compressed sensing
* Elastic Boundary Projection for 3D Medical Image Segmentation
* ELASTIC: Improving CNNs With Dynamic Scaling Policies
* Empirical Minimum Bayes Risk Prediction
* Empirical Minimum Bayes Risk Prediction: How to Extract an Extra Few % Performance from Vision Models with Just Three More Parameters
* Error Factor Analysis for Wild Scene Image-Labelling
* Estimation of 3D Category-Specific Object Structure: Symmetry, Manhattan and/or Multiple Images
* Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding
* Explicit Occlusion Reasoning for Multi-person 3D Human Pose Estimation
* Exploiting Symmetry and/or Manhattan Properties for 3D Object Structure Estimation from Single and Multiple Images
* Exploring Simple 3D Multi-Object Tracking for Autonomous Driving
* External Attention Assisted Multi-Phase Splenic Vascular Injury Segmentation With Limited Data
* Extremum Principle for Shape from Contour, An
* Fast and Simple Algorithm for Producing Candidate Regions, A
* Feature Denoising for Improving Adversarial Robustness
* Feature Extraction from Faces Using Deformable Templates
* Few-Shot Image Recognition by Predicting Parameters from Activations
* Fingerprint Theorems for Zero-Crossings
* Fingerprints Theorems
* FORMS: A Flexible Object Recognition and Modelling System
* framework for shape representation and recognition, A
* Fundamental Bounds on Edge Detection: An Information Theoretic Evaluation of Different Edge Cues
* Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking
* G-factors: Relating Distributions on Features to Distributions on Images
* Generalized Deformable Models, Statistical Physics and Matching Problems
* Generalized Ordering Constraint for Stereo Correspondence, A
* Generating Multiple Diverse Hypotheses for Human 3D Pose Consistent with 2D Joint Detections
* Generation and Comprehension of Unambiguous Object Descriptions
* Generative Model Based Approach to Motion Segmentation, A
* generic viewpoint assumption and planar bias, The
* Genetic CNN
* Geometric Neural Phrase Pooling: Modeling the Spatial Co-Occurrence of Neurons
* Graph-shifts: Natural image labeling by dynamic hierarchical computing
* Ground-Truth Data Set and Baseline Evaluations for Base-Detail Separation Algorithms at the Part Level
* Grouped Spatial-Temporal Aggregation for Efficient Action Recognition
* Grouping Iso-Velocity Points for Ego-Motion Recovery
* Guest Editorial Introduction to the Special Issue on Large Scale and Nonlinear Similarity Learning for Intelligent Video Analysis
* Guest Editorial: Geometry, Lighting, Motion, and Learning
* Guest Editorial: Statistical and Computational Theories of Vision: Modeling, Learning, Sampling and Computing, Part I
* High-Level and Generic Models for Visual Search: When Does High Level Knowledge Help?
* HOP: Hierarchical object parsing
* Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding
* Identity Preserve Transform: Understand What Activity Classification Models Have Learnt
* Image Parsing: Unifying Segmentation, Detection, and Recognition
* Image Warping for Shape Recovery and Recognition
* Imbalanced regression for intensity series of pain expression from videos by regularizing spatio-temporal face nets
* Impossible Shaded Images
* Improving Transferability of Adversarial Examples With Input Diversity
* In Defense of Image Pre-Training for Spatiotemporal Recognition
* In Defense of Online Models for Video Instance Segmentation
* Inference and learning with hierarchical compositional models
* Inference and Learning with Hierarchical Shape Models
* InterActive: Inter-Layer Activeness Propagation
* Iterative Reorganization With Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation Learning
* Joint Multi-person Pose Estimation and Semantic Part Segmentation
* Joint Object and Part Segmentation Using Deep Learned Potentials
* JSSR: A Joint Synthesis, Segmentation, and Registration System for 3D Multi-modal Image Alignment of Large-scale Pathological CT Scans
* k-means Mask Transformer
* KGBR Viewpoint-Lighting Ambiguity and its Resolution by Generic Constraints, The
* KGBR viewpointlighting ambiguity, The
* Label-Free Liver Tumor Segmentation
* Large sample group independent component analysis of functional magnetic resonance imaging using anatomical atlas-based reduction and bootstrapped clustering
* Latent hierarchical structural learning for object detection
* Learning a dictionary of deformable patches using GPUs
* Learning a Dictionary of Shape Epitomes with Applications to Image Labeling
* Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
* Learning From Synthetic Animals
* Learning from Synthetic Vehicles
* Learning from Temporal Gradient for Semi-supervised Action Recognition
* Learning Inductive Attention Guidance for Partially Supervised Pancreatic Ductal Adenocarcinoma Prediction
* Learning Like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images
* Learning Object Representations from Lighting Variations
* Learning Part Segmentation through Unsupervised Domain Adaptation from Synthetic Vehicles
* Learning to Refine 3D Human Pose Sequences
* Lite Vision Transformer with Enhanced Self-Attention
* Local, Global, and Multilevel Stereo Matching
* Localizing Occluders with Compositional Convolutional Networks
* Manhattan World: Compass Direction from a Single Image by Bayesian Inference
* Mask Guided Matting via Progressive Refinement Network
* Masked Feature Prediction for Self-Supervised Visual Pre-Training
* Massively Parallel Implementations of Theories for Apparent Motion
* Mathematical Analysis of the Motion Coherence Theory, A
* Max Margin AND/OR Graph learning for parsing the human body
* Max Margin Learning of Hierarchical Configural Deformable Templates (HCDTs) for Efficient Object Parsing and Pose Estimation
* MaX-DeepLab: End-to-End Panoptic Segmentation with Mask Transformers
* Mean-Field Phase Transistions and Correlation Functions for Gibbs Random Fields
* Mining 3D Key-Pose-Motifs for Action Recognition
* model for the estimate of local velocity, A
* Modeling deformable gradient compositions for single-image super-resolution
* Modeling Image Patches with a Generic Dictionary of Mini-epitomes
* Motion Coherence Theory, The
* Motion Estimation by Swendsen-Wang Cuts
* MRF Labeling with a Graph-Shifts Algorithm
* Multi-context Attention for Human Pose Estimation
* Multi-scale Spatially-Asymmetric Recalibration for Image Classification
* Multi-stage Multi-recursive-input Fully Convolutional Networks for Neuronal Boundary Detection
* Multilevel Enhancement and Detection of Stereo Disparity Surfaces
* NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction
* Neural Architecture Search for Lightweight Non-Local Networks
* Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization
* Non-Rigid Motion and Regge Calculus
* Non-Rigid Point Set Registration by Preserving Global and Local Structures
* Novel Linelet-Based Representation for Line Segment Detection, A
* Nuisance-Label Supervision: Robustness Improvement by Free Labels
* Object as Hotspots: An Anchor-free 3d Object Detection Approach via Firing of Hotspots
* Occluded Video Instance Segmentation: A Benchmark
* Occlusions and Binocular Stereo
* One Shot Learning via Compositions of Meaningful Patches
* OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images
* Order Parameters for Detecting Target Curves in Images: When Does High Level Knowledge Help?
* Order Parameters for Minimax Entropy Distributions: When does High Level Knowledge Help?
* OVIS: Occluded Video Instance Segmentation
* Parsing occluded people by flexible compositions
* Parsing Semantic Parts of Cars Using Graphical Models and Segment Appearance Consistency
* Part and appearance sharing: Recursive Compositional Models for multi-view, Multi-Object Detection
* PartImageNet: A Large, High-Quality Dataset of Parts
* PASCAL Boundaries: A Semantic Boundary Dataset with a Deep Semantic Boundary Detector
* Patchattack: A Black-box Texture-based Attack with Reinforcement Learning
* PCL: Proposal Cluster Learning for Weakly Supervised Object Detection
* Perspective Projection Invariants
* Perturb-and-MAP random fields: Using discrete optimization to learn and sample from energy models
* Point-Level Region Contrast for Object Detection Pre-Training
* Prior-Aware Neural Network for Partially-Supervised Multi-Organ Segmentation
* Progressive Neural Architecture Search
* Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement
* Recovering Object Surfaces from Viewed Changes in Surface Texture Patterns
* Recurrent Multimodal Interaction for Referring Image Segmentation
* Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans
* Recurrent Saliency Transformation Network: Incorporating Multi-stage Visual Cues for Small Organ Segmentation
* Recursive Compositional Models for Vision: Description and Review of Recent Work
* Recursive compositional models: Representation, learning, and inference
* Recursive Segmentation and Recognition Templates for Image Parsing
* Region Competition and its Analysis: A Unified Theory for Image Segmentation
* Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
* Region-based temporally consistent video post-processing
* Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
* Regularized Solution to Edge Detection, A
* Regularizing face verification nets for pain intensity regression
* Relating image warping to 3D geometrical deformations
* Resisting Large Data Variations via Introspective Transformation Network
* Rigidity and Smoothness of Motion
* Robust Category-Level 6D Pose Estimation with Coarse-to-Fine Rendering of Neural Features
* Robust Estimation of 3D Human Poses from a Single Image
* Robust Estimation of Nonrigid Transformation for Point Set Registration
* Robust Face Detection via Learning Small Faces on Hard Images
* Robust Instance Segmentation through Reasoning about Multi-Object Occlusion
* Robust Object Detection Under Occlusion With Context-Aware CompositionalNets
* Robust Point Matching via Vector Field Consensus
* Robust Region Grouping via Internal Patch Statistics
* Role of Context for Object Detection and Semantic Segmentation in the Wild, The
* Scale invariance without scale selection
* Scale-Space SIFT flow
* ScaleNet: Guiding Object Proposal Generation in Supermarkets and Beyond
* Scaling and Fingerprint Theorems for Zero-Crossings
* Scaling Theorems for Zero-Crossings
* Scene-Domain Active Part Models for Object Representation
* Secrets of Salient Object Segmentation, The
* Segmentation for Classification of Screening Pancreatic Neuroendocrine Tumors
* Segmenting by Seeking the Symmetry Axis
* Self-Supervised Pillar Motion Learning for Autonomous Driving
* Semantic Image Segmentation with Task-Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform
* Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints From Limited Training Data
* Semantic part segmentation using compositional model combining shape and appearance
* Semantic-Aware Knowledge Preservation for Zero-Shot Sketch-Based Image Retrieval
* Semi-Supervised 3D Abdominal Multi-Organ Segmentation Via Deep Multi-Planar Co-Training
* Semi-Supervised Sparse Representation Based Classification for Face Recognition With Insufficient Labeled Samples
* Shape and Albedo from Multiple Images Using Integrability
* Shape from Shading via the Fusion of Specular and Lambertian Image Components
* Shape from Shading, Occlusion and Texture
* Shape Matching and Recognition: Using Generative Models and Informative Features
* Shape matching and registration by data-driven EM
* Shape Reconstructability Measure of Object Part Importance with Applications to Object Detection and Localization, A
* Signfinder: Using Color to Detect, Localize and Identify Informational Signs
* Simple Data Mixing Prior for Improving Self-Supervised Learning, A
* Simulated Adversarial Testing of Face Recognition Models
* Single Image Super-resolution Using Deformable Patches
* Single-Shot Object Detection with Enriched Semantics
* Smoothest Velocity Field and Token Matching Schemes, The
* Snapshot Distillation: Teacher-Student Optimization in One Generation
* SORT: Second-Order Response Transform for Visual Recognition
* Sources from Shading
* SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection
* Statistical and Geometrical Approaches to Visual Motion Analysis
* statistical approach to multi-scale edge detection, A
* Statistical Cues for Domain Specific Image Segmentation with Performance Analysis
* Statistical edge detection: learning and evaluating edge cues
* Statistical Morphology and Bayesian Reconstruction
* Stereo and Controlled Movement
* Stereo and Eye Movement
* Stereo integration, mean field theory and psychophysics
* Stereopsis And Eye-Movement
* STFlow: Self-Taught Optical Flow Estimation Using Pseudo Labels
* Structure-perceptron learning of a hierarchical log-linear model
* Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning
* Surface Shape from Warping
* SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual Question Answering
* Symmetric Non-rigid Structure from Motion for Category-Specific Object Structure Estimation
* Synthesize Then Compare: Detecting Failures and Anomalies for Semantic Segmentation
* Synthesizing Attributes with Unreal Engine for Fine-grained Activity Analysis
* Texture Segmentation by Minimizing Vector-Valued Energy Functionals: The Coupled-Membrane Model
* Time-Efficient Cascade for Real-Time Object Detection: With applications for the visually impaired, A
* Towards a theory of compositional learning and encoding of objects
* Towards unified depth and semantic prediction from a single image
* Towards Unified Object Detection and Semantic Segmentation
* Training a general purpose deformable template
* TransMix: Attend to Mix for Vision Transformers
* Universal Physical Camouflage Attacks on Object Detectors
* UnrealCV: Connecting Computer Vision to Unreal Engine
* UnrealStereo: Controlling Hazardous Factors to Analyze Stereo Vision
* Unsupervised Learning of Object Deformation Models
* Unsupervised learning of optical flow with patch consistency and occlusion estimation
* Unsupervised Learning of Probabilistic Grammar-Markov Models for Object Categories
* Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
* Unsupervised Learning of Probabilistic Object Models (POMs) for Object Classification, Segmentation, and Recognition Using Knowledge Propagation
* Unsupervised Structure Learning: Hierarchical Recursive Composition, Suspicious Coincidence and Competitive Exclusion
* V-NAS: Neural Architecture Search for Volumetric Medical Image Segmentation
* ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation
* Visual Motion Estimation and Prediction: A Probabilistic Network Model for Temporal Coherence
* Weakly Supervised Instance Segmentation for Videos with Temporal Mask Consistency
* Weakly Supervised Region Proposal Network and Object Detection
* Weakly-and Semi-Supervised Learning of a Deep Convolutional Network for Semantic Image Segmentation
* Zero Crossings on Lines of Curvature
* Zoom Better to See Clearer: Human and Object Parsing with Hierarchical Auto-Zoom Net
Includes: Yuille, A.L.[Alan L.] Yuille, A.L.
308 for Yuille, A.L.
Yuille, A.Y.[Alan Y.]
Co Author Listing * CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
* Occlusion Boundary Detection Using Pseudo-depth