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 1151–1160 of 2042 papers

Title	Date	Tasks	Status
(RF)^2 -- Random Forest Random Field	Dec 1, 2010	Object Recognition	—Unverified
RIDE: Reversal Invariant Descriptor Enhancement	Dec 1, 2015	Object Recognition	—Unverified
RIGOR: Reusing Inference in Graph Cuts for Generating Object Regions	Jun 1, 2014	Object RecognitionSegmentation	—Unverified
RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression	Jan 21, 2025	Autonomous DrivingObject Recognition	—Unverified
RMNv2: Reduced Mobilenet V2 for CIFAR10	Jan 8, 2020	Autonomous VehiclesData Augmentation	—Unverified
Robot In a Room: Toward Perfect Object Recognition in Closed Environments	Jul 9, 2015	ObjectObject Recognition	—Unverified
Robust Domain Generalization for Multi-modal Object Recognition	Aug 11, 2024	Domain GeneralizationMulti-Label Classification	—Unverified
Robust Intrinsic and Extrinsic Calibration of RGB-D Cameras	Jan 20, 2017	Object Recognition	—Unverified
Robustness of Humans and Machines on Object Recognition with Extreme Image Transformations	May 9, 2022	Object Recognition	—Unverified
Are Transformers More Robust? Towards Exact Robustness Verification for Transformers	Feb 8, 2022	Autonomous DrivingObject 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