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 1771–1780 of 2042 papers

Title	Date	Tasks	Status
Feature Evaluation of Deep Convolutional Neural Networks for Object Recognition and Detection	Sep 25, 2015	General ClassificationObject Recognition	—Unverified
Analyzing structural characteristics of object category representations from their semantic-part distributions	Sep 15, 2015	ObjectObject Recognition	—Unverified
On Binary Classification with Single-Layer Convolutional Neural Networks	Sep 13, 2015	Binary ClassificationClassification	—Unverified
DeepSat - A Learning framework for Satellite Imagery	Sep 11, 2015	ClassificationDenoising	CodeCode Available
Hierarchical Deep Learning Architecture For 10K Objects Classification	Sep 7, 2015	ClassificationDeep Learning	—Unverified
Unsupervised Cross-Domain Recognition by Identifying Compact Joint Subspaces	Sep 5, 2015	Domain AdaptationObject Recognition	—Unverified
Object Recognition from Short Videos for Robotic Perception	Sep 4, 2015	ObjectObject Recognition	—Unverified
Visual Classifier Prediction by Distributional Semantic Embedding of Text Descriptions	Sep 1, 2015	Domain AdaptationImage Captioning	—Unverified
Generating Image Descriptions with Gold Standard Visual Inputs: Motivation, Evaluation and Baselines	Sep 1, 2015	Image RetrievalObject Recognition	—Unverified
From the Virtual to the RealWorld: Referring to Objects in Real-World Spatial Scenes	Sep 1, 2015	Object RecognitionText Generation	—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