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 1–10 of 2042 papers

Title	Date	Tasks	Status	Hype
GeoMag: A Vision-Language Model for Pixel-level Fine-Grained Remote Sensing Image Parsing	Jul 8, 2025	Language ModelingLanguage Modelling	—Unverified	0
Out-of-distribution detection in 3D applications: a review	Jul 1, 2025	Autonomous DrivingNavigate	—Unverified	0
SASep: Saliency-Aware Structured Separation of Geometry and Feature for Open Set Learning on Point Clouds	Jun 16, 2025	3D Object RecognitionObject Recognition	CodeCode Available	0
Continual Hyperbolic Learning of Instances and Classes	Jun 12, 2025	Continual LearningObject Recognition	—Unverified	0
DCIRNet: Depth Completion with Iterative Refinement for Dexterous Grasping of Transparent and Reflective Objects	Jun 11, 2025	Depth CompletionDepth Estimation	—Unverified	0
Aligning Text, Images, and 3D Structure Token-by-Token	Jun 9, 2025	3D Object RecognitionInstruction Following	—Unverified	0
STSBench: A Spatio-temporal Scenario Benchmark for Multi-modal Large Language Models in Autonomous Driving	Jun 6, 2025	Autonomous DrivingAutonomous Vehicles	CodeCode Available	1
Feature-Based Lie Group Transformer for Real-World Applications	Jun 5, 2025	ObjectObject Recognition	—Unverified	0
EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects	Jun 4, 2025	Event-based visionObject Recognition	—Unverified	0
Explicitly Modeling Subcortical Vision with a Neuro-Inspired Front-End Improves CNN Robustness	Jun 3, 2025	Data AugmentationObject Recognition	—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