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 131–140 of 2042 papers

Title	Date	Tasks	Status	Hype
Partial success in closing the gap between human and machine vision	Jun 14, 2021	Image ClassificationObject Recognition	CodeCode Available	1
Person Re-Identification with a Locally Aware Transformer	Jun 7, 2021	Object RecognitionPerson Re-Identification	CodeCode Available	1
Convolutional Neural Networks with Gated Recurrent Connections	Jun 5, 2021	object-detectionObject Detection	CodeCode Available	1
DOCTOR: A Simple Method for Detecting Misclassification Errors	Jun 4, 2021	Object RecognitionSentiment Analysis	CodeCode Available	1
Superpixel-based Knowledge Infusion in Deep Neural Networks for Image Classification	May 20, 2021	Face RecognitionGraph Neural Network	CodeCode Available	1
Are Convolutional Neural Networks or Transformers more like human vision?	May 15, 2021	BIG-bench Machine LearningObject Recognition	CodeCode Available	1
This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks	May 5, 2021	Explainable artificial intelligenceImage Classification	CodeCode Available	1
RelTransformer: A Transformer-Based Long-Tail Visual Relationship Recognition	Apr 24, 2021	Image CaptioningObject Recognition	CodeCode Available	1
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition	Apr 8, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
F-SIOL-310: A Robotic Dataset and Benchmark for Few-Shot Incremental Object Learning	Mar 23, 2021	Incremental LearningObject	CodeCode Available	1

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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