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 731–740 of 2042 papers

Title	Date	Tasks	Status
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds	Nov 28, 2021	3D Shape Classificationgraph construction	—Unverified
Efficient Anomaly Detection Using Self-Supervised Multi-Cue Tasks	Nov 24, 2021	Anomaly DetectionColorization	—Unverified
Inducing Functions through Reinforcement Learning without Task Specification	Nov 23, 2021	Decision Makingimage-classification	—Unverified
Object Recognition by a Minimally Pre-Trained System in the Process of Environment Exploration	Nov 23, 2021	ObjectObject Recognition	—Unverified
Adversarial Examples on Segmentation Models Can be Easy to Transfer	Nov 22, 2021	Adversarial RobustnessAttribute	—Unverified
ShapeY: Measuring Shape Recognition Capacity Using Nearest Neighbor Matching	Nov 16, 2021	ObjectObject Recognition	—Unverified
The Neural Correlates of Image Texture in the Human Vision Using Magnetoencephalography	Nov 16, 2021	Object Recognition	—Unverified
Occluded Video Instance Segmentation: Dataset and ICCV 2021 Challenge	Nov 15, 2021	Instance SegmentationObject Recognition	—Unverified
6D Pose Estimation with Combined Deep Learning and 3D Vision Techniques for a Fast and Accurate Object Grasping	Nov 11, 2021	3D Object Recognition6D Pose Estimation	—Unverified
Unsupervised Spiking Instance Segmentation on Event Data using STDP	Nov 9, 2021	Event-based visionFace Detection	—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