SOTAVerified

Object Categorization

Object categorization identifies which label, from a given set, best corresponds to an image region defined by an input image and bounding box.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 11–20 of 80 papers

TitleStatusHype
Vocabulary-informed Zero-shot and Open-set LearningCode0
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN ModelsCode0
Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks—0
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning FrameworkCode0
Webly Supervised Concept Expansion for General Purpose Vision Models—0
Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorizationCode0
Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces—0
Local-HDP: Interactive Open-Ended 3D Object Categorization in Real-Time Robotic Scenarios—0
IAUnet: Global Context-Aware Feature Learning for Person Re-IdentificationCode0
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object RecognitionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Unified-IOXLCategorization (ablation)61.7—Unverified
2GPV-2Categorization (ablation)54.7—Unverified
3CLIPCategorization (ablation)48.1—Unverified
4OFA_LargeCategorization (ablation)22.6—Unverified