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 1311–1320 of 2042 papers

Title	Date	Tasks	Status
Integrating Knowledge and Reasoning in Image Understanding	Jun 24, 2019	Object RecognitionQuestion Answering	—Unverified
Integration of 3D Object Recognition and Planning for Robotic Manipulation: A Preliminary Report	Jul 29, 2013	3D Object RecognitionObject Recognition	—Unverified
Interactive Open-Ended Learning for 3D Object Recognition	Dec 19, 2019	3D Object RecognitionObject	—Unverified
Interactive Segmentation on RGBD Images via Cue Selection	Jun 1, 2016	Image RetrievalImage Segmentation	—Unverified
Interpretable Graph Capsule Networks for Object Recognition	Dec 3, 2020	Adversarial RobustnessObject	—Unverified
Interpretable multimodal fusion networks reveal mechanisms of brain cognition	Jun 16, 2020	Object Recognition	—Unverified
Interpreting Convolutional Neural Networks Through Compression	Nov 7, 2017	Object Recognition	—Unverified
Interpreting the Residual Stream of ResNet18	Jul 7, 2024	Object Recognition	—Unverified
Introducing Memory and Association Mechanism into a Biologically Inspired Visual Model	Jul 4, 2013	Object RecognitionPosition	—Unverified
Introducing VaDA: Novel Image Segmentation Model for Maritime Object Segmentation Using New Dataset	Jul 12, 2024	Autonomous NavigationImage Segmentation	—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