Object Recognition

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.

( Image credit: Tensorflow Object Detection API )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1631–1640 of 2042 papers

Title	Date	Tasks	Status
Performance Evaluation of Learned 3D Features	Sep 15, 2019	Object Recognition	—Unverified
Performance Evaluation of Raster Based Shape Vectors in Object Recognition	Mar 28, 2014	ObjectObject Recognition	—Unverified
Performance of object recognition in wearable videos	Sep 10, 2020	MarketingObject	—Unverified
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex	Jun 6, 2023	ObjectObject Recognition	—Unverified
Periocular Recognition Using CNN Features Off-the-Shelf	Sep 17, 2018	Object Recognition	—Unverified
Persistence-based Structural Recognition	Jun 1, 2014	3D Shape Classification3D Shape Retrieval	—Unverified
Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning	Aug 9, 2017	Object RecognitionSemantic Segmentation	—Unverified
Physics-based Scene-level Reasoning for Object Pose Estimation in Clutter	Jun 25, 2018	object-detectionObject Detection	—Unverified
PiCoDes: Learning a Compact Code for Novel-Category Recognition	Dec 1, 2011	ObjectObject Recognition	—Unverified
PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Edge-Preserving Coherence	May 13, 2015	Image SegmentationObject Recognition	—Unverified

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All datasets shape bias CIFAR10-DVS N-Caltech 101 ObjectNet (All classes)ObjectNet (ImageNet classes)ObjectNet (ImageNet classes, trained on ImageNet)DVS128 Gesture MECCANO N-CARS

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Imagen	shape bias	98.7	—	Unverified
2	Stable Diffusion	shape bias	92.7	—	Unverified
3	Parti	shape bias	91.7	—	Unverified
4	ViT-22B-384	shape bias	86.4	—	Unverified
5	ViT-22B-560	shape bias	83.8	—	Unverified
6	CLIP (ViT-B)	shape bias	79.9	—	Unverified
7	ViT-22B-224	shape bias	78	—	Unverified
8	ResNet-50 (L2 eps 5.0 adv trained)	shape bias	69.5	—	Unverified
9	ResNet-50 (with strong augmentations)	shape bias	62.2	—	Unverified
10	SWSL (ResNeXt-101)	shape bias	49.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.55	—	Unverified
2	SSNN	Accuracy (% )	78.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	85.62	—	Unverified
2	SSNN	Accuracy (% )	79.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	18.75	—	Unverified
2	yun	Top 5 Accuracy	14.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	DY	Top 5 Accuracy	0.08	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ObjectNet-Baseline	Top 5 Accuracy	52.24	—	Unverified
2	AJ2021	Top 5 Accuracy	27.68	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SSNN	Accuracy (% )	94.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Faster-RCNN	mAP	30.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Spike-VGG11	Accuracy (% )	96	—	Unverified