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 461–470 of 2042 papers

Title	Date	Tasks	Status
Geo-locating Road Objects using Inverse Haversine Formula with NVIDIA Driveworks	Jan 15, 2024	Autonomous DrivingAutonomous Vehicles	—Unverified
Application of 2D Homography for High Resolution Traffic Data Collection using CCTV Cameras	Jan 14, 2024	Camera CalibrationObject Recognition	—Unverified
Meta-forests: Domain generalization on random forests with meta-learning	Jan 9, 2024	Domain GeneralizationMeta-Learning	—Unverified
Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition	Jan 3, 2024	DescriptiveLanguage Modeling	—Unverified
Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Network	Jan 2, 2024	Data AugmentationEvent data classification	—Unverified
Layerwise complexity-matched learning yields an improved model of cortical area V2	Dec 18, 2023	Object Recognition	—Unverified
Object Recognition from Scientific Document based on Compartment Refinement Framework	Dec 14, 2023	ArticlesDocument Layout Analysis	—Unverified
Representational constraints underlying similarity between task-optimized neural systems	Dec 13, 2023	Object Recognition	—Unverified
Exploring Novel Object Recognition and Spontaneous Location Recognition Machine Learning Analysis Techniques in Alzheimer's Mice	Dec 12, 2023	Object RecognitionPose Estimation	CodeCode Available
The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates	Dec 10, 2023	ObjectObject Recognition	—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