Papers Generalized Zero-Shot Learning
“Generalized Zero-Shot Learning” 태그가 달린 논문 167편 · 필터 해제
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 CloudsVisual and Semantic Prompt Collaboration for Generalized Zero-Shot Learning
Generalized zero-shot learning aims to recognize both seen and unseen classes with the help of semantic information that is shared among different classes. It inevitably requires consistent visual-semantic alignment. Exi…
Generalized Zero-Shot LearningZero-Shot LearningExtremely Simple Out-of-distribution Detection for Audio-visual Generalized Zero-shot Learning
Zero-shot Learning(ZSL) attains knowledge transfer from seen classes to unseen classes by exploring auxiliary category information, which is a promising yet difficult research topic. In this field, Audio-Visual Generaliz…
Binary ClassificationGeneralized Zero-Shot LearningOut-of-Distribution DetectionOut of Distribution (OOD) Detection+2Generalized Zero-Shot Classification via Semantics-Free Inter-Class Feature Generation
Generalized Zero-Shot Learning (GZSL) addresses the challenge of classifying unseen classes in the presence of seen classes by leveraging semantic attributes to bridge the gap for unseen classes. However, in image ba…
Classificationcross-modal alignmentGeneralized Zero-Shot Learningzero-shot-classification+1PSVMA+: Exploring Multi-granularity Semantic-visual Adaption for Generalized Zero-shot Learning
Generalized zero-shot learning (GZSL) endeavors to identify the unseen categories using knowledge from the seen domain, necessitating the intrinsic interactions between the visual features and attribute semantic features…
AttributeDiversityGeneralized Zero-Shot LearningZero-Shot LearningRevCD -- Reversed Conditional Diffusion for Generalized Zero-Shot Learning
In Generalized Zero-Shot Learning (GZSL), we aim to recognize both seen and unseen categories using a model trained only on seen categories. In computer vision, this translates into a classification problem, where knowle…
Generalized Zero-Shot LearningTransfer LearningZero-Shot LearningOut-Of-Distribution Detection for Audio-visual Generalized Zero-Shot Learning: A General Framework
Generalized Zero-Shot Learning (GZSL) is a challenging task requiring accurate classification of both seen and unseen classes. Within this domain, Audio-visual GZSL emerges as an extremely exciting yet difficult task, gi…
Generalized Zero-Shot LearningOut-of-Distribution DetectionOut of Distribution (OOD) DetectionZero-Shot LearningLeveraging Foundation Models for Zero-Shot IoT Sensing
Deep learning models are increasingly deployed on edge Internet of Things (IoT) devices. However, these models typically operate under supervised conditions and fail to recognize unseen classes different from training. T…
Data AugmentationGeneralized Zero-Shot LearningZero-Shot LearningAudio-visual Generalized Zero-shot Learning the Easy Way
Audio-visual generalized zero-shot learning is a rapidly advancing domain that seeks to understand the intricate relations between audio and visual cues within videos. The overarching goal is to leverage insights from se…
Generalized Zero-Shot LearningZero-Shot LearningCLIP-Decoder : ZeroShot Multilabel Classification using Multimodal CLIP Aligned Representation
Multi-label classification is an essential task utilized in a wide variety of real-world applications. Multi-label zero-shot learning is a method for classifying images into multiple unseen categories for which no traini…
ClassificationDecoderGeneralized Zero-Shot LearningMulti-Label Classification+5Exploring Data Efficiency in Zero-Shot Learning with Diffusion Models
Zero-Shot Learning (ZSL) aims to enable classifiers to identify unseen classes by enhancing data efficiency at the class level. This is achieved by generating image features from pre-defined semantics of unseen classes. …
Generalized Zero-Shot LearningZero-Shot LearningCICA: Content-Injected Contrastive Alignment for Zero-Shot Document Image Classification
Zero-shot learning has been extensively investigated in the broader field of visual recognition, attracting significant interest recently. However, the current work on zero-shot learning in document image classification …
Document Classificationdocument-image-classificationDocument Image ClassificationGeneralized Zero-Shot Learning+3Dual Expert Distillation Network for Generalized Zero-Shot Learning
Zero-shot learning has consistently yielded remarkable progress via modeling nuanced one-to-one visual-attribute correlation. Existing studies resort to refining a uniform mapping function to align and correlate the samp…
AttributeGeneralized Zero-Shot LearningZero-Shot Learning`Eyes of a Hawk and Ears of a Fox': Part Prototype Network for Generalized Zero-Shot Learning
Current approaches in Generalized Zero-Shot Learning (GZSL) are built upon base models which consider only a single class attribute vector representation over the entire image. This is an oversimplification of the proces…
AttributeGeneralized Zero-Shot LearningZero-Shot LearningAudio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models
Audio-visual zero-shot learning methods commonly build on features extracted from pre-trained models, e.g. video or audio classification models. However, existing benchmarks predate the popularization of large multi-moda…
Audio ClassificationGeneralized Zero-Shot LearningZero-Shot Learning