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

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Showing 51–60 of 80 papers

TitleStatusHype
Effective Deterministic Initialization for k-Means-Like Methods via Local Density Peaks Searching—0
Emergence of Selective Invariance in Hierarchical Feed Forward Networks—0
Enhanced Biologically Inspired Model for Image Recognition Based on a Novel Patch Selection Method with Moment—0
Evolution in Groups: A deeper look at synaptic cluster driven evolution of deep neural networks—0
Finding Optimal Combination of Kernels using Genetic Programming—0
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
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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