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 61–70 of 80 papers

TitleStatusHype
Thesis: Multiple Kernel Learning for Object Categorization—0
Finding Optimal Combination of Kernels using Genetic Programming—0
RotationNet: Joint Object Categorization and Pose Estimation Using Multiviews from Unsupervised ViewpointsCode0
Convolutional Models for Joint Object Categorization and Pose Estimation—0
Basic Level Categorization Facilitates Visual Object Recognition—0
Classifier Adaptation at Prediction Time—0
Bio-inspired Unsupervised Learning of Visual Features Leads to Robust Invariant Object Recognition—0
Towards Learning free Naive Bayes Nearest Neighbor-based Domain Adaptation—0
A Hierarchical Approach for Joint Multi-view Object Pose Estimation and Categorization—0
A Unified Semantic Embedding: Relating Taxonomies and Attributes—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