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 176–200 of 2042 papers

Title	Date	Tasks	Status	Hype
Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations	Mar 6, 2023	Contrastive LearningObject Recognition	CodeCode Available	1
Learning Semi-supervised Gaussian Mixture Models for Generalized Category Discovery	May 10, 2023	Contrastive Learningimage-classification	CodeCode Available	1
Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?	Jan 2, 2020	Object Recognition	CodeCode Available	1
Category-Prompt Refined Feature Learning for Long-Tailed Multi-Label Image Classification	Aug 15, 2024	image-classificationImage Classification	CodeCode Available	1
Bilateral Event Mining and Complementary for Event Stream Super-Resolution	May 16, 2024	Object RecognitionSuper-Resolution	CodeCode Available	1
LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition	Sep 22, 2023	ObjectObject Recognition	CodeCode Available	1
Attribution in Scale and Space	Apr 3, 2020	AttributeObject Recognition	CodeCode Available	1
Matching the Neuronal Representations of V1 is Necessary to Improve Robustness in CNNs with V1-like Front-ends	Oct 16, 2023	Object Recognition	CodeCode Available	1
Billion-scale semi-supervised learning for image classification	May 2, 2019	ClassificationGeneral Classification	CodeCode Available	1
MiKASA: Multi-Key-Anchor & Scene-Aware Transformer for 3D Visual Grounding	Mar 5, 2024	3D visual groundingDecision Making	CodeCode Available	1
Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering	Jul 6, 2021	Active LearningObject Recognition	CodeCode Available	1
Causal Transportability for Visual Recognition	Apr 26, 2022	image-classificationImage Classification	CodeCode Available	1
Multiple Instance Detection Network with Online Instance Classifier Refinement	Apr 1, 2017	Multiple Instance LearningObject	CodeCode Available	1
Neural Regression, Representational Similarity, Model Zoology & Neural Taskonomy at Scale in Rodent Visual Cortex	Dec 1, 2021	BenchmarkingObject Recognition	CodeCode Available	1
N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras	Dec 2, 2021	ClassificationObject	CodeCode Available	1
Contemplating real-world object classification	Mar 8, 2021	ClassificationData Augmentation	CodeCode Available	1
Offline Meta-Reinforcement Learning with Advantage Weighting	Aug 13, 2020	Machine TranslationMeta-Learning	CodeCode Available	1
When and how CNNs generalize to out-of-distribution category-viewpoint combinations	Jul 15, 2020	DiversityObject Recognition	CodeCode Available	1
On the Challenges of Open World Recognitionunder Shifting Visual Domains	Jul 9, 2021	Domain GeneralizationObject Recognition	CodeCode Available	1
ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition	Apr 8, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax	Jun 18, 2020	image-classificationImage Classification	CodeCode Available	1
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1
Part-guided Relational Transformers for Fine-grained Visual Recognition	Dec 28, 2022	Fine-Grained Image ClassificationFine-Grained Visual Recognition	CodeCode Available	1
3D ShapeNets: A Deep Representation for Volumetric Shapes	Jun 22, 2014	3D Point Cloud Classification3D Shape Representation	CodeCode Available	1
Rehearsal-Free Continual Learning over Small Non-I.I.D. Batches	Jul 8, 2019	class-incremental learningClass Incremental Learning	CodeCode Available	1

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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