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SotA/Computer Vision/Object Recognition

Object Recognition

17 benchmarks2042 papers

Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.

<span style="color:grey; opacity: 0.6">( Image credit: Tensorflow Object Detection API )</span>

Benchmarks

Object Recognition on shape bias

shape bias

Object Recognition on CIFAR10-DVS

Accuracy (% )

Object Recognition on N-Caltech 101

Accuracy (% )

Object Recognition on ObjectNet (All classes)

Top 5 AccuracyTop 1 Accuracy

Object Recognition on ObjectNet (ImageNet classes)

Top 5 AccuracyTop 1 Accuracy

Object Recognition on ObjectNet (ImageNet classes, trained on ImageNet)

Top 5 AccuracyTop 1 Accuracy

Object Recognition on Cube Engraving

Accuracy

Object Recognition on DVS128 Gesture

Accuracy (% )

Object Recognition on MECCANO

mAP

Object Recognition on N-CARS

Accuracy (% )

Object Recognition on SHREC11, Split10-10

Per-Class Accuracy

Object Recognition on SHREC11, Split16-4

Per-Class Accuracy

Object Recognition on ModelNet40

Accuracy

Object Recognition on Photo-Art-50

Overall Accuracy