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 1571–1580 of 2042 papers

Title	Date	Tasks	Status
A large comparison of feature-based approaches for buried target classification in forward-looking ground-penetrating radar	Feb 9, 2017	General ClassificationObject Recognition	—Unverified
ImageNet MPEG-7 Visual Descriptors - Technical Report	Feb 1, 2017	General Classificationimage-classification	—Unverified
Deep Network Guided Proof Search	Jan 24, 2017	Deep LearningGame of Go	—Unverified
Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features	Jan 23, 2017	Brain DecodingObject	—Unverified
Robust Intrinsic and Extrinsic Calibration of RGB-D Cameras	Jan 20, 2017	Object Recognition	—Unverified
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition	Jan 19, 2017	Action RecognitionFine-grained Action Recognition	—Unverified
Synthetic to Real Adaptation with Generative Correlation Alignment Networks	Jan 19, 2017	Domain AdaptationObject Recognition	—Unverified
Incremental Learning for Robot Perception through HRI	Jan 17, 2017	Incremental LearningObject	—Unverified
Bandwidth limited object recognition in high resolution imagery	Jan 16, 2017	Objectobject-detection	—Unverified
What are the visual features underlying human versus machine vision?	Jan 10, 2017	DiagnosticObject	—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