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 641–650 of 2042 papers

Title	Date	Tasks	Status	Hype
Knowledge-driven Active Learning	Oct 15, 2021	Active LearningMulti-Label Classification	CodeCode Available	0
Oriented Feature Alignment for Fine-grained Object Recognition in High-Resolution Satellite Imagery	Oct 13, 2021	Objectobject-detection	—Unverified	0
In Silico Modelling of Neurodegeneration Using Deep Convolutional Neural Networks	Oct 12, 2021	Object Recognition	—Unverified	0
Out-of-distribution robustness: Limited image exposure of a four-year-old is enough to outperform ResNet-50	Oct 12, 2021	Object Recognition	—Unverified	0
Bio-inspired learnable divisive normalization for ANNs	Oct 12, 2021	Decoderimage-classification	—Unverified	0
Recurrent Attention Models with Object-centric Capsule Representation for Multi-object Recognition	Oct 11, 2021	DecoderObject	CodeCode Available	0
X-model: Improving Data Efficiency in Deep Learning with A Minimax Model	Oct 9, 2021	Age Estimationmodel	—Unverified	0
ZSpeedL -- Evaluating the Performance of Zero-Shot Learning Methods using Low-Power Devices	Oct 9, 2021	Object RecognitionZero-Shot Learning	—Unverified	0
Explainability-Aware One Point Attack for Point Cloud Neural Networks	Oct 8, 2021	3D Object RecognitionAdversarial Robustness	CodeCode Available	1
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition	Oct 8, 2021	Emotion RecognitionObject	—Unverified	0

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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