Generalized Zero-Shot Learning
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Benchmarks
SUN Attribute
AwA2
CUB-200-2011
Oxford 102 Flower
OntoNotes
S3DIS
ScanNet
SemanticKITTI
aPY
aPY - 0-Shot
Most implemented
Feature Generating Networks for Zero-Shot Learning
Contrastive Embedding for Generalized Zero-Shot Learning
Class Normalization for (Continual)? Generalized Zero-Shot Learning
Zero-Shot Learning with Common Sense Knowledge Graphs
A Deep Dive into Adversarial Robustness in Zero-Shot Learning
Papers
A statistical approach to bias in zero-shot learning: the lens of handwriting recognition
Generalized zero-shot learning (GZSL) has emerged as an important paradigm for visual recognition systems that must generalize to classes that were not observed during training. Traditional GZSL techniques are limited by…
Generalized Zero-Shot LearningHandwriting RecognitionOn Aligning Hierarchical Standardized Embedding for Audio-visual Generalized Zero-shot Learning
Audio-visual Generalized Zero-shot Learning (AV-GZSL) is a challenging task that aims to classify both seen and unseen objects or scenes by integrating data from audio and visual modalities. Recent studies primarily focu…
Generalized Zero-Shot LearningToward a More Ethical Facial Age Estimation: A Generalized Zero-Shot Benchmark Without Training on Children's Data
Age estimation from facial images typically relies on training data that includes images of minors, a practice that raises ethical, legal, and privacy concerns and that child-data governance frameworks explicitly advise …
Generalized Zero-Shot LearningAge EstimationAdversarial Robustness in Zero-Shot Learning:An Empirical Study on Class and Concept-Level Vulnerabilities
Zero-shot Learning (ZSL) aims to enable image classifiers to recognize images from unseen classes that were not included during training. Unlike traditional supervised classification, ZSL typically relies on learning a m…
Generalized Zero-Shot LearningAdversarial RobustnessGZSL-MoE: Apprentissage G{é}n{é}ralis{é} Z{é}ro-Shot bas{é} sur le M{é}lange d'Experts pour la Segmentation S{é}mantique de Nuages de Points 3DAppliqu{é} {à} un Jeu de Donn{é}es d'Environnement de Collaboration Humain-Robot
Generative Zero-Shot Learning approach (GZSL) has demonstrated significant potential in 3D point cloud semantic segmentation tasks. GZSL leverages generative models like GANs or VAEs to synthesize realistic features (rea…
Generalized Zero-Shot Learning3D Semantic SegmentationGeneralized Zero-Shot Learning for Point Cloud Segmentation with Evidence-Based Dynamic Calibration
Generalized zero-shot semantic segmentation of 3D point clouds aims to classify each point into both seen and unseen classes. A significant challenge with these models is their tendency to make biased predictions, often …
Zero-Shot Semantic SegmentationGeneralized Zero-Shot LearningPoint Cloud SegmentationPoint Clouds