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 1876–1900 of 2042 papers

Title	Date	Tasks	Status
Intrinsic dimension estimation for locally undersampled data	Jun 18, 2019	Object Recognition	CodeCode Available
A Computational Acquisition Model for Multimodal Word Categorization	May 12, 2022	Language Acquisitionmodel	CodeCode Available
Analysis and Optimization of Convolutional Neural Network Architectures	Jul 31, 2017	Data AugmentationObject Recognition	CodeCode Available
Semi-supervised Ranking for Object Image Blur Assessment	Jul 13, 2022	ObjectObject Recognition	CodeCode Available
ViSTa Dataset: Do vision-language models understand sequential tasks?	Nov 20, 2024	MinecraftObject Recognition	CodeCode Available
A Multi-viewpoint Outdoor Dataset for Human Action Recognition	Oct 7, 2021	Action RecognitionFace Recognition	CodeCode Available
Investigating Negation in Pre-trained Vision-and-language Models	Nov 1, 2021	NegationObject Recognition	CodeCode Available
Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks	Nov 1, 2024	Object Recognition	CodeCode Available
Real Classification by Description: Extending CLIP's Limits of Part Attributes Recognition	Dec 18, 2024	AttributeDescriptive	CodeCode Available
Investigating the Nature of 3D Generalization in Deep Neural Networks	Apr 19, 2023	Object Recognition	CodeCode Available
Target-Aware Generative Augmentations for Single-Shot Adaptation	May 22, 2023	AttributeObject Recognition	CodeCode Available
Targeted View-Invariant Adversarial Perturbations for 3D Object Recognition	Dec 17, 2024	3D Object RecognitionAdversarial Robustness	CodeCode Available
Real-Time Correlation Tracking via Joint Model Compression and Transfer	Jul 23, 2019	Computational EfficiencyCPU	CodeCode Available
Dense and Diverse Capsule Networks: Making the Capsules Learn Better	May 10, 2018	General Classificationimage-classification	CodeCode Available
Fast Feature Fool: A data independent approach to universal adversarial perturbations	Jul 18, 2017	Object Recognition	CodeCode Available
SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer Learning	Sep 23, 2024	Image RetrievalMetric Learning	CodeCode Available
Seq-NMS for Video Object Detection	Feb 26, 2016	General ClassificationObject	CodeCode Available
Task-Aware Monocular Depth Estimation for 3D Object Detection	Sep 17, 2019	3D Object Detection3D Object Recognition	CodeCode Available
Is Second-order Information Helpful for Large-scale Visual Recognition?	Mar 23, 2017	Object Recognition	CodeCode Available
Associative Alignment for Few-shot Image Classification	Dec 11, 2019	ClassificationDomain Adaptation	CodeCode Available
Delta-encoder: an effective sample synthesis method for few-shot object recognition	Jun 12, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available
Faster gaze prediction with dense networks and Fisher pruning	Jan 17, 2018	Gaze EstimationGaze Prediction	CodeCode Available
RECALL: Rehearsal-free Continual Learning for Object Classification	Sep 29, 2022	ClassificationContinual Learning	CodeCode Available
Kernel Manifold Alignment	Apr 9, 2015	Computational EfficiencyDomain Adaptation	CodeCode Available
Recent Advances in Neural Program Synthesis	Feb 7, 2018	Object RecognitionProgram induction	CodeCode Available

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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