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 831–840 of 2042 papers

Title	Date	Tasks	Status
Discriminative Multi-Modal Feature Fusion for RGBD Indoor Scene Recognition	Jun 1, 2016	Image SegmentationObject Recognition	—Unverified
Discriminatively Trained Sparse Code Gradients for Contour Detection	Dec 1, 2012	Contour DetectionDictionary Learning	—Unverified
Brain-Like Object Recognition Neural Networks are more robustness to common corruptions	Oct 9, 2020	Object Recognition	—Unverified
Generalization Boosted Adapter for Open-Vocabulary Segmentation	Sep 13, 2024	Object RecognitionSegmentation	—Unverified
Generalized Adaptive Dictionary Learning via Domain Shift Minimization	Oct 31, 2014	ClassificationDictionary Learning	—Unverified
Generalized K-fan Multimodal Deep Model with Shared Representations	Mar 26, 2015	Information RetrievalObject Recognition	—Unverified
Generalized Lasso based Approximation of Sparse Coding for Visual Recognition	Dec 1, 2011	Object Recognition	—Unverified
Generalized Multi-view Embedding for Visual Recognition and Cross-modal Retrieval	May 31, 2016	Cross-Modal RetrievalImage Retrieval	—Unverified
Graph Convolutional Networks for Classification with a Structured Label Space	Oct 12, 2017	ClassificationDocument Classification	—Unverified
Discriminative Ferns Ensemble for Hand Pose Recognition	Jun 1, 2014	ClassificationGeneral Classification	—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