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 1201–1210 of 2042 papers

Title	Date	Tasks	Status	Hype
Causal importance of orientation selectivity for generalization in image recognition	May 1, 2019	image-classificationImage Classification	CodeCode Available	0
Contextual Recurrent Convolutional Model for Robust Visual Learning	May 1, 2019	Fine-Grained Image ClassificationGeneral Classification	—Unverified	0
Learning what and where to attend with humans in the loop	May 1, 2019	DiagnosticImage Categorization	—Unverified	0
Learning to Find Common Objects Across Few Image Collections	Apr 29, 2019	Few-Shot LearningObject	CodeCode Available	0
Deep Multi-View Learning using Neuron-Wise Correlation-Maximizing Regularizers	Apr 25, 2019	3D Object RecognitionGeneral Classification	—Unverified	0
Pointing Novel Objects in Image Captioning	Apr 25, 2019	DecoderImage Captioning	—Unverified	0
Improved visible to IR image transformation using synthetic data augmentation with cycle-consistent adversarial networks	Apr 25, 2019	Data AugmentationObject Recognition	—Unverified	0
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond	Apr 25, 2019	Instance SegmentationObject Detection	CodeCode Available	2
Context-Aware Zero-Shot Learning for Object Recognition	Apr 24, 2019	ObjectObject Recognition	—Unverified	0
PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras	Apr 24, 2019	Dimensionality Reductionfeature selection	—Unverified	0

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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