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 31–40 of 80 papers

TitleStatusHype
From N to N+1: Multiclass Transfer Incremental Learning—0
Grassmannian Discriminant Maps (GDM) for Manifold Dimensionality Reduction with Application to Image Set Classification—0
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine—0
Humans can decipher adversarial images—0
Learning Mid-Level Features and Modeling Neuron Selectivity for Image Classification—0
Local-HDP: Interactive Open-Ended 3D Object Categorization in Real-Time Robotic Scenarios—0
PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras—0
Multiple Manifolds Metric Learning with Application to Image Set Classification—0
Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning—0
Object categorization in finer levels requires higher spatial frequencies, and therefore takes longer—0
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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