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 901–910 of 2042 papers

Title	Date	Tasks	Status
Hierarchical Novelty Detection for Visual Object Recognition	Apr 2, 2018	Generalized Zero-Shot LearningNovelty Detection	—Unverified
Hierarchical Object Representation for Open-Ended Object Category Learning and Recognition	Dec 1, 2016	3D Object RecognitionObject	—Unverified
Hierarchical Piecewise-Constant Super-regions	May 19, 2016	DenoisingForm	—Unverified
Hierarchical Prototype Learning for Zero-Shot Recognition	Oct 24, 2019	AttributeImage Captioning	—Unverified
Data-driven Verification of DNNs for Object Recognition	Jul 17, 2024	Image SegmentationObject	—Unverified
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition	Jan 19, 2017	Action RecognitionFine-grained Action Recognition	—Unverified
Highlight Timestamp Detection Model for Comedy Videos via Multimodal Sentiment Analysis	May 28, 2021	Multimodal Sentiment AnalysisObject Recognition	—Unverified
Histograms of Pattern Sets for Image Classification and Object Recognition	Jun 1, 2014	BinarizationGeneral Classification	—Unverified
Discovering Novel Actions from Open World Egocentric Videos with Object-Grounded Visual Commonsense Reasoning	May 26, 2023	Object RecognitionVisual Commonsense Reasoning	—Unverified
BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning	Nov 19, 2017	Object Recognition	—Unverified

Show:10 25 50

← PrevPage 91 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