Vats, A.[Arpita]
* 2022: Key Point-Based Driver Activity Recognition
* 2023: 1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
* 2023: Enhancing Retail Checkout through Video Inpainting, YOLOv8 Detection, and DeepSort Tracking
Vats, D.
* 2011: Hybrid Small Animal Imaging System Combining Magnetic Resonance Imaging With Fluorescence Tomography Using Single Photon Avalanche Diode Detectors
Vats, E.[Ekta]
* 2015: Fuzzy human motion analysis: A review
* 2019: Embedded Prototype Subspace Classification: A Subspace Learning Framework
Vats, K.
* 2018: HyperStackNet: A Hyper Stacked Hourglass Deep Convolutional Neural Network Architecture for Joint Player and Stick Pose Estimation in Hockey
* 2019: KPTransfer: Improved Performance and Faster Convergence from Keypoint Subset-Wise Domain Transfer in Human Pose Estimation
* 2019: Pose-Projected Action Recognition Hourglass Network (PARHN) in Soccer
* 2019: Two-Stream Action Recognition in Ice Hockey using Player Pose Sequences and Optical Flows
* 2020: Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutions
* 2021: DeepDarts: Modeling Keypoints as Objects for Automatic Scorekeeping in Darts using a Single Camera
* 2021: Puck localization and multi-task event recognition in broadcast hockey videos
* 2022: Ice hockey player identification via transformers and weakly supervised learning
* 2022: Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-person Human Pose Estimation
Includes: Vats, K. Vats, K.[Kanav]
9 for Vats, K.
Vats, S.[Shashank]
* 2020: Novel Ensemble Framework for Face Search, A
Vats, V.[Vanshika]
* 2023: Adversarial Examples with Specular Highlights
Vats, V.K.[Vibhas K.]
* 2024: GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo
Vatsa, A.[Avimanyou]
* 2016: Extracting complex lesion phenotypes in Zea mays
* 2016: opinion on imaging challenges in phenotyping field crops, An
Vatsa, M.[Mayank]
* 2004: Iris Based Human Verification Algorithms
* 2006: Dempster-Shafer Theory Based Classifier Fusion for Improved Fingerprint Verification Performance
* 2007: Age Transformation for Improving Face Recognition Performance
* 2007: Mosaicing Scheme for Pose-Invariant Face Recognition, A
* 2007: Unification of Evidence Theoretic Fusion Algorithms: A Case Study in Level-2 and Level-3 Fingerprint Features
* 2008: Integrated multilevel image fusion and match score fusion of visible and infrared face images for robust face recognition
* 2008: Likelihood ratio in a SVM framework: Fusing linear and non-linear face classifiers
* 2008: Multiclass mv-granular soft support vector machine: A case study in dynamic classifier selection for multispectral face recognition
* 2008: Quality Induced Fingerprint Identification using Extended Feature Set
* 2009: Context Switching Algorithm for Selective Multibiometric Fusion
* 2009: Effect of plastic surgery on face recognition: A preliminary study
* 2009: Face recognition with disguise and single gallery images
* 2009: Feature based RDWT watermarking for multimodal biometric system
* 2009: Online learning in biometrics: A case study in face classifier update
* 2009: Simultaneous latent fingerprint recognition: A preliminary study
* 2009: Unification of Evidence Theoretic Fusion Algorithms: A Case Study in Level-2 and Level-3 Fingerprint Features
* 2010: Biometric classifier update using online learning: A case study in near infrared face verification
* 2010: Quality-Based Fusion for Multichannel Iris Recognition
* 2011: Evolutionary granular approach for recognizing faces altered due to plastic surgery
* 2011: Quality assessment based denoising to improve face recognition performance
* 2012: Biometric match score fusion using RVM: A case study in multi-unit iris recognition
* 2012: Incremental subclass discriminant analysis: A case study in face recognition
* 2012: Matching cross-resolution face images using co-transfer learning
* 2013: Bacteria Foraging Fusion for Face Recognition across Age Progression
* 2013: Boosting local descriptors for matching composite and digital face images
* 2013: Can Combining Demographics and Biometrics Improve De-Duplication Performance?
* 2013: Can holistic representations be used for face biometric quality assessment?
* 2013: Computationally Efficient Face Spoofing Detection with Motion Magnification
* 2013: On rank aggregation for face recognition from videos
* 2014: Biometric quality: a review of fingerprint, iris, and face
* 2014: Improving Cross-Resolution Face Matching Using Ensemble-Based Co-Transfer Learning
* 2014: Leap signature recognition using HOOF and HOT features
* 2014: On cross spectral periocular recognition
* 2014: On Effectiveness of Histogram of Oriented Gradient Features for Visible to Near Infrared Face Matching
* 2014: On Iris Spoofing Using Print Attack
* 2015: QFuse: Online learning framework for adaptive biometric system
* 2016: At-a-distance person recognition via combining ocular features
* 2016: Discriminative FaceTopics for face recognition via latent Dirichlet allocation
* 2016: Effect of illicit drug abuse on face recognition
* 2016: Face anti-spoofing with multifeature videolet aggregation
* 2016: Face identification from low resolution near-infrared images
* 2016: Fingerprint sensor classification via Melange of handcrafted features
* 2016: Improving classifier fusion via Pool Adjacent Violators normalization
* 2016: Incremental granular relevance vector machine: A case study in multimodal biometrics
* 2016: Low rank group sparse representation based classifier for pose variation
* 2016: Mobile periocular matching with pre-post cataract surgery
* 2016: On incremental semi-supervised discriminant analysis
* 2016: Sketch Recognition: What Lies Ahead?
* 2017: Class sparsity signature based Restricted Boltzmann Machine
* 2017: Face Presentation Attack with Latex Masks in Multispectral Videos
* 2017: Face Sketch Matching via Coupled Deep Transform Learning
* 2017: Face Verification via Class Sparsity Based Supervised Encoding
* 2017: Group sparse autoencoder
* 2017: Hierarchical Representation Learning for Kinship Verification
* 2017: Transfer Learning Based Evolutionary Algorithm for Composite Face Sketch Recognition
* 2018: CrowdFaceDB: Database and benchmarking for face verification in crowd
* 2018: Disguised Faces in the Wild
* 2018: Exploring Bias in Primate Face Detection and Recognition
* 2018: Face Recognition for Newborns, Toddlers, and Pre-School Children: A Deep Learning Approach
* 2018: Fusion of Handcrafted and Deep Learning Features for Large-Scale Multiple Iris Presentation Attack Detection
* 2018: Identity Aware Synthesis for Cross Resolution Face Recognition
* 2018: Iris Presentation Attack via Textured Contact Lens in Unconstrained Environment
* 2018: Learning Structure and Strength of CNN Filters for Small Sample Size Training
* 2018: On Detecting Domestic Abuse via Faces
* 2018: Person Authentication Using Head Images
* 2018: Scattering Transform for Matching Surgically Altered Face Images
* 2018: SegDenseNet: Iris Segmentation for Pre-and-Post Cataract Surgery
* 2018: Unconstrained Fingerphoto Database
* 2018: Unraveling Human Perception of Facial Aging Using Eye Gaze
* 2019: Are you eligible? Predicting adulthood from face images via Class Specific Mean Autoencoder
* 2019: AUTO-G: Gesture Recognition in the Crowd for Autonomous Vehicle
* 2019: Detecting and Mitigating Adversarial Perturbations for Robust Face Recognition
* 2019: Disguised Faces in the Wild 2019
* 2019: Dual Directed Capsule Network for Very Low Resolution Image Recognition
* 2019: Latent Fingerprint Enhancement Using Generative Adversarial Networks
* 2019: On Learning Density Aware Embeddings
* 2019: Residual Codean Autoencoder for Facial Attribute Analysis
* 2019: Supervised Mixed Norm Autoencoder for Kinship Verification in Unconstrained Videos
* 2019: Triplet Transform Learning for Automated Primate Face Recognition
* 2020: Attribute Aware Filter-Drop for Bias-Invariant Classification
* 2020: Detecting Face2Face Facial Reenactment in Videos
* 2020: Detecting GANs and Retouching based Digital Alterations via DAD-HCNN
* 2020: DNDNet: Reconfiguring CNN for Adversarial Robustness
* 2020: Generalized Zero-Shot Learning via Over-Complete Distribution
* 2020: Noise is Inside Me! Generating Adversarial Perturbations with Noise Derived from Natural Filters
* 2020: On Privacy Preserving Anonymization of Finger-selfies
* 2020: Role of Sign and Direction of Gradient on the Performance of CNN, The
* 2021: AECNet: Attentive EfficientNet For Crowd Counting
* 2021: Age Gap Reducer-GAN for Recognizing Age-Separated Faces
* 2021: Attack Agnostic Adversarial Defense via Visual Imperceptible Bound
* 2021: Attention Aware Debiasing for Unbiased Model Prediction
* 2021: Cognitive data augmentation for adversarial defense via pixel masking
* 2021: Discriminative shared transform learning for sketch to image matching
* 2021: Dual Sensor Indian Masked Face Dataset
* 2021: Generalized Iris Presentation Attack Detection Algorithm under Cross-Database Settings
* 2021: Improving face recognition performance using TeCS2 dictionary
* 2021: Indian Masked Faces in the Wild Dataset
* 2021: Intelligent and Adaptive Mixup Technique for Adversarial Robustness
* 2021: MD-CSDNetwork: Multi-Domain Cross Stitched Network for Deepfake Detection
* 2021: MixNet for Generalized Face Presentation Attack Detection
* 2021: RGB-D Face Recognition using Reconstruction based Shared Representation
* 2021: Unravelling the Effect of Image Distortions for Biased Prediction of Pre-trained Face Recognition Models
* 2021: When Sketch Face Recognition Meets Mask Obfuscation: Database and Benchmark
* 2022: Benchmarking Robustness Beyond LP Norm Adversaries
* 2022: Crafting Adversarial Perturbations via Transformed Image Component Swapping
* 2022: DeriveNet for (Very) Low Resolution Image Classification
* 2022: DeSI: Deepfake Source Identifier for Social Media
* 2022: Disguise Resilient Face Verification
* 2022: Enhanced iris presentation attack detection via contraction-expansion CNN
* 2022: Exploring Robustness Connection between Artificial and Natural Adversarial Examples
* 2022: MTCD: Cataract detection via near infrared eye images
* 2022: Multi-task driven explainable diagnosis of COVID-19 using chest X-ray images
* 2022: Robust IRIS Presentation Attack Detection Through Stochastic Filter Noise
* 2023: Are Face Detection Models Biased?
* 2023: DF-Platter: Multi-Face Heterogeneous Deepfake Dataset
* 2023: PhygitalNet: Unified Face Presentation Attack Detection via One-Class Isolation Learning
* 2023: Robustness Against Gradient based Attacks through Cost Effective Network Fine-Tuning
* 2023: Uniform misclassification loss for unbiased model prediction
* 2024: SynthProv: Interpretable Framework for Profiling Identity Leakage
Includes: Vatsa, M.[Mayank] Vatsa, M.
119 for Vatsa, M.
Vatsavai, R.[Raju]
* 2016: Guest editorial: big spatial data
Vatsavai, R.R.[Ranga Raju]
* 2008: Learning Scheme for Recognizing Sub-classes from Model Trained on Aggregate Classes, A
* 2008: Overhead image statistics
* 2010: Modeling spatial dependencies in high-resolution overhead imagery
* 2010: Supervised semantic classification for nuclear proliferation monitoring
* 2011: hybrid classification scheme for mining multisource geospatial data, A
* 2015: Multitemporal data mining: From biomass monitoring to nuclear proliferation detection
* 2020: Learning a distance function with a Siamese network to localize anomalies in videos
* 2021: Local Clustering with Mean Teacher for Semi-supervised learning
* 2022: Deep Residual Network with Multi-Image Attention for Imputing Under Clouds in Satellite Imagery
* 2022: Survey of Single-Scene Video Anomaly Detection, A
Includes: Vatsavai, R.R.[Ranga Raju] Vatsavai, R.R. Vatsavai, R.R.[R. Raju]
10 for Vatsavai, R.R.