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 591–600 of 2042 papers

Title	Date	Tasks	Status
Teaching What You Should Teach: A Data-Based Distillation Method	Dec 11, 2022	Data AugmentationKnowledge Distillation	—Unverified
State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions	Dec 10, 2022	MemorizationObject Recognition	—Unverified
Beyond Object Recognition: A New Benchmark towards Object Concept Learning	Dec 6, 2022	AttributeObject	—Unverified
Recognizing Object by Components with Human Prior Knowledge Enhances Adversarial Robustness of Deep Neural Networks	Dec 4, 2022	Adversarial RobustnessInductive Bias	CodeCode Available
Extreme Image Transformations Affect Humans and Machines Differently	Nov 30, 2022	Object Recognition	—Unverified
Coordinating Cross-modal Distillation for Molecular Property Prediction	Nov 30, 2022	Graph RegressionGraph Representation Learning	—Unverified
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation	Nov 30, 2022	DiversityInstruction Following	—Unverified
Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition	Nov 30, 2022	AllObject	—Unverified
Metric Learning as a Service with Covariance Embedding	Nov 28, 2022	Information RetrievalMetric Learning	—Unverified
Learning to Learn: How to Continuously Teach Humans and Machines	Nov 28, 2022	class-incremental learningClass Incremental Learning	—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