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 881–890 of 2042 papers

Title	Date	Tasks	Status	Hype
Rotation-Invariant Local-to-Global Representation Learning for 3D Point Cloud	Oct 7, 2020	3D Object RecognitionData Augmentation	—Unverified	0
Learning to Represent Image and Text with Denotation Graph	Oct 6, 2020	AttributeImage Retrieval	—Unverified	0
A Study for Universal Adversarial Attacks on Texture Recognition	Oct 4, 2020	Adversarial AttackDeep Learning	—Unverified	0
Evaluating Progress on Machine Learning for Longitudinal Electronic Healthcare Data	Oct 2, 2020	BIG-bench Machine LearningDecompensation	—Unverified	0
Transformers: State-of-the-Art Natural Language Processing	Oct 1, 2020	Image ClassificationObject Recognition	CodeCode Available	0
Robust and Efficient Post-Processing for Video Object Detection (REPP)	Oct 1, 2020	Autonomous DrivingDense Object Detection	CodeCode Available	1
Training CNNs in Presence of JPEG Compression: Multimedia Forensics vs Computer Vision	Sep 25, 2020	Face DetectionGeneral Classification	—Unverified	0
Neurocoder: Learning General-Purpose Computation Using Stored Neural Programs	Sep 24, 2020	Continual LearningObject Recognition	—Unverified	0
Robust and efficient post-processing for video object detection	Sep 23, 2020	Autonomous DrivingObject	CodeCode Available	1
Unsupervised Feature Learning for Event Data: Direct vs Inverse Problem Formulation	Sep 23, 2020	Object RecognitionRepresentation Learning	—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