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 891–900 of 2042 papers

Title	Date	Tasks	Status
Modeling Human Development: Effects of Blurred Vision on Category Learning in CNNs	Jan 1, 2021	ClassificationGeneral Classification	—Unverified
Sample Balancing for Improving Generalization under Distribution Shifts	Jan 1, 2021	Domain AdaptationObject Recognition	—Unverified
On the Robustness of Sentiment Analysis for Stock Price Forecasting	Jan 1, 2021	BIG-bench Machine LearningObject Recognition	—Unverified
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods.	Jan 1, 2021	Object RecognitionRepresentation Learning	—Unverified
Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream	Jan 1, 2021	Developmental LearningObject Recognition	CodeCode Available
Visual Probing and Correction of Object Recognition Models with Interactive user feedback	Dec 29, 2020	Autonomous DrivingObject	CodeCode Available
Warping of Radar Data into Camera Image for Cross-Modal Supervision in Automotive Applications	Dec 23, 2020	Direction of Arrival EstimationObject Recognition	—Unverified
Flexible deep transfer learning by separate feature embeddings and manifold alignment	Dec 22, 2020	Domain AdaptationObject Recognition	—Unverified
Simultaneous View and Feature Selection for Collaborative Multi-Robot Perception	Dec 17, 2020	feature selectionObject Recognition	—Unverified
Projected Distribution Loss for Image Enhancement	Dec 16, 2020	DeblurringDemosaicking	CodeCode Available

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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