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 31–40 of 80 papers

TitleStatusHype
Best sources forward: domain generalization through source-specific nets—0
Sparse, Collaborative, or Nonnegative Representation: Which Helps Pattern Classification?—0
Data augmentation instead of explicit regularizationCode0
Recurrent Convolutional Fusion for RGB-D Object RecognitionCode0
Multiple Manifolds Metric Learning with Application to Image Set Classification—0
A Simple Riemannian Manifold Network for Image Set Classification—0
Visual Object Categorization Based on Hierarchical Shape Motifs Learned From Noisy Point Cloud Decompositions—0
VISER: Visual Self-Regularization—0
Convolutional Networks for Object Category and 3D Pose Estimation from 2D Images—0
Dual Skipping Networks—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