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 1011–1020 of 2042 papers

Title	Date	Tasks	Status
Evaluation of Environmental Conditions on Object Detection using Oriented Bounding Boxes for AR Applications	Jun 29, 2023	object-detectionObject Detection	—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
CogNav: Cognitive Process Modeling for Object Goal Navigation with LLMs	Dec 11, 2024	Large Language ModelObject	—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
Evaluating Progress on Machine Learning for Longitudinal Electronic Healthcare Data	Oct 2, 2020	BIG-bench Machine LearningDecompensation	—Unverified
Evaluating Multimodal Language Models as Visual Assistants for Visually Impaired Users	Mar 28, 2025	Object RecognitionReading Comprehension	—Unverified
Applications of Probabilistic Programming (Master's thesis, 2015)	May 31, 2016	Object RecognitionProbabilistic Programming	—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