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 1681–1690 of 2042 papers

Title	Date	Tasks	Status
Image Style Transfer Using Convolutional Neural Networks	Jun 1, 2016	Image GenerationObject Recognition	CodeCode Available
Towards ontology driven learning of visual concept detectors	May 31, 2016	Active LearningObject Recognition	—Unverified
Applications of Probabilistic Programming (Master's thesis, 2015)	May 31, 2016	Object RecognitionProbabilistic Programming	—Unverified
Generalized Multi-view Embedding for Visual Recognition and Cross-modal Retrieval	May 31, 2016	Cross-Modal RetrievalImage Retrieval	—Unverified
Latent Bi-constraint SVM for Video-based Object Recognition	May 31, 2016	ObjectObject Recognition	—Unverified
Parametric Exponential Linear Unit for Deep Convolutional Neural Networks	May 30, 2016	Object RecognitionScene Understanding	—Unverified
Semi-supervised Zero-Shot Learning by a Clustering-based Approach	May 29, 2016	ClusteringObject Recognition	—Unverified
Pairwise Decomposition of Image Sequences for Active Multi-View Recognition	May 26, 2016	Object Recognition	—Unverified
FPNN: Field Probing Neural Networks for 3D Data	May 20, 2016	3D geometry3D Object Recognition	CodeCode Available
Hierarchical Piecewise-Constant Super-regions	May 19, 2016	DenoisingForm	—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