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 1661–1670 of 2042 papers

Title	Date	Tasks	Status
A Too-Good-to-be-True Prior to Reduce Shortcut Reliance	Feb 12, 2021	Object Recognitionvalid	—Unverified
A Transfer Learning Approach to Cross-Modal Object Recognition: From Visual Observation to Robotic Haptic Exploration	Jan 18, 2020	ObjectObject Recognition	—Unverified
Attention Mechanisms for Object Recognition with Event-Based Cameras	Jul 25, 2018	Event-based visionObject Recognition	—Unverified
AttoNets: Compact and Efficient Deep Neural Networks for the Edge via Human-Machine Collaborative Design	Mar 18, 2019	object-detectionObject Detection	—Unverified
Attribute-Based Classification for Zero-Shot Visual Object Categorization	Jul 30, 2013	AttributeClassification	—Unverified
ATZSL: Defensive Zero-Shot Recognition in the Presence of Adversaries	Oct 24, 2019	Image CaptioningObject Recognition	—Unverified
AU Dataset for Visuo-Haptic Object Recognition for Robots	Dec 27, 2021	ObjectObject Recognition	—Unverified
Audiovisual Highlight Detection in Videos	Feb 11, 2021	Highlight DetectionObject Recognition	—Unverified
Auditing ImageNet: Towards a Model-driven Framework for Annotating Demographic Attributes of Large-Scale Image Datasets	May 3, 2019	Object Recognition	—Unverified
Augmenting Image Annotation: A Human-LMM Collaborative Framework for Efficient Object Selection and Label Generation	Mar 14, 2025	Object Recognition	—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