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 1431–1440 of 2042 papers

Title	Date	Tasks	Status	Hype
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks	Dec 1, 2017	Action RecognitionMetric Learning	—Unverified	0
Learning to Segment Moving Objects	Dec 1, 2017	Motion EstimationMotion Segmentation	—Unverified	0
Label Efficient Learning of Transferable Representations across Domains and Tasks	Nov 30, 2017	Action RecognitionMetric Learning	—Unverified	0
Relation Networks for Object Detection	Nov 30, 2017	Objectobject-detection	CodeCode Available	1
Memory Aware Synapses: Learning what (not) to forget	Nov 27, 2017	Lifelong learningObject Recognition	CodeCode Available	0
Context Augmentation for Convolutional Neural Networks	Nov 22, 2017	General Classificationimage-classification	—Unverified	0
Glitch Classification and Clustering for LIGO with Deep Transfer Learning	Nov 20, 2017	ClassificationClustering	—Unverified	0
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning	Nov 19, 2017	Object Recognition	—Unverified	0
ADVISE: Symbolism and External Knowledge for Decoding Advertisements	Nov 17, 2017	ClusteringImage Captioning	—Unverified	0
Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment	Nov 16, 2017	Domain AdaptationObject Recognition	CodeCode Available	0

Show:10 25 50

← PrevPage 144 of 205Next →

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