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 1811–1820 of 2042 papers

Title	Date	Tasks	Status
On the Relationship Between Visual Attributes and Convolutional Networks	Jun 1, 2015	AttributeObject Recognition	—Unverified
Semi-Supervised Domain Adaptation With Subspace Learning for Visual Recognition	Jun 1, 2015	Domain AdaptationObject Recognition	—Unverified
Data-Driven 3D Voxel Patterns for Object Category Recognition	Jun 1, 2015	ObjectObject Recognition	—Unverified
A Dynamic Programming Approach for Fast and Robust Object Pose Recognition From Range Images	Jun 1, 2015	Object RecognitionPose Estimation	—Unverified
Is Object Localization for Free? - Weakly-Supervised Learning With Convolutional Neural Networks	Jun 1, 2015	General ClassificationObject	—Unverified
DeepContour: A Deep Convolutional Feature Learned by Positive-Sharing Loss for Contour Detection	Jun 1, 2015	Contour DetectionImage Segmentation	—Unverified
Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition	Jun 1, 2015	ObjectObject Recognition	—Unverified
CURL: Co-trained Unsupervised Representation Learning for Image Classification	May 29, 2015	ClassificationGeneral Classification	—Unverified
Texture Synthesis Using Convolutional Neural Networks	May 27, 2015	ObjectObject Recognition	CodeCode Available
The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition	May 17, 2015	Action RecognitionMulti-class 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