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 181–190 of 2042 papers

Title	Date	Tasks	Status	Hype	Score
On the Challenges of Open World Recognitionunder Shifting Visual Domains	Jul 9, 2021	Domain GeneralizationObject Recognition	CodeCode Available	1	5
On the Element-Wise Representation and Reasoning in Zero-Shot Image Recognition: A Systematic Survey	Aug 9, 2024	Object Recognition	CodeCode Available	1	5
DesCo: Learning Object Recognition with Rich Language Descriptions	Jun 24, 2023	Language ModelingLanguage Modelling	CodeCode Available	1	5
DetMatch: Two Teachers are Better Than One for Joint 2D and 3D Semi-Supervised Object Detection	Mar 17, 2022	object-detectionObject Detection	CodeCode Available	1	5
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1	5
Exploit Clues from Views: Self-Supervised and Regularized Learning for Multiview Object Recognition	Mar 28, 2020	ObjectObject Recognition	CodeCode Available	1	5
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches	Jul 8, 2019	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
Describing Textures in the Wild	Nov 14, 2013	Material RecognitionObject Recognition	CodeCode Available	1	5
PartImageNet: A Large, High-Quality Dataset of Parts	Dec 2, 2021	Activity RecognitionFew-Shot Learning	CodeCode Available	1	5
F-SIOL-310: A Robotic Dataset and Benchmark for Few-Shot Incremental Object Learning	Mar 23, 2021	Incremental LearningObject	CodeCode Available	1	5

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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