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 991–1000 of 2042 papers

Title	Date	Tasks	Status
Boosting Object Recognition in Point Clouds by Saliency Detection	Nov 6, 2019	Object RecognitionSaliency Detection	—Unverified
Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation	Jun 6, 2017	Object RecognitionSegmentation	—Unverified
Incorporating Semantic Attention in Video Description Generation	May 1, 2018	Image CaptioningImage Classification	—Unverified
Incorporating Structural Alternatives and Sharing into Hierarchy for Multiclass Object Recognition and Detection	Feb 3, 2015	Object Recognitionvalid	—Unverified
Incorporating Textual Evidence in Visual Storytelling	Nov 21, 2019	Object RecognitionStory Generation	—Unverified
Incremental Learning for Robot Perception through HRI	Jan 17, 2017	Incremental LearningObject	—Unverified
Deep Learning with Energy-efficient Binary Gradient Cameras	Dec 3, 2016	Deep LearningFace Detection	—Unverified
Inducing Functions through Reinforcement Learning without Task Specification	Nov 23, 2021	Decision Makingimage-classification	—Unverified
Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19	Nov 23, 2020	Defect Detectionobject-detection	—Unverified
ADLDA: A Method to Reduce the Harm of Data Distribution Shift in Data Augmentation	May 11, 2024	Data AugmentationDomain Adaptation	—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