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 1801–1825 of 2042 papers

Title	Date	Tasks	Status
SVM and ELM: Who Wins? Object Recognition with Deep Convolutional Features from ImageNet	Jun 8, 2015	General Classificationimage-classification	—Unverified
Monocular SLAM Supported Object Recognition	Jun 4, 2015	ObjectObject Recognition	—Unverified
Exploiting an Oracle that Reports AUC Scores in Machine Learning Contests	Jun 3, 2015	BIG-bench Machine LearningBinary Classification	—Unverified
Hyper-Class Augmented and Regularized Deep Learning for Fine-Grained Image Classification	Jun 1, 2015	Fine-Grained Image ClassificationGeneral Classification	—Unverified
Regularizing Max-Margin Exemplars by Reconstruction and Generative Models	Jun 1, 2015	Object Recognition	—Unverified
Recurrent Convolutional Neural Network for Object Recognition	Jun 1, 2015	ObjectObject Recognition	—Unverified
Zero-Shot Object Recognition by Semantic Manifold Distance	Jun 1, 2015	AttributeObject	—Unverified
Automatically Discovering Local Visual Material Attributes	Jun 1, 2015	ObjectObject Recognition	—Unverified
Beyond Spatial Pooling: Fine-Grained Representation Learning in Multiple Domains	Jun 1, 2015	ObjectObject Recognition	—Unverified
A Novel Locally Linear KNN Model for Visual Recognition	Jun 1, 2015	Action RecognitionDensity Estimation	—Unverified
On the Relationship Between Visual Attributes and Convolutional Networks	Jun 1, 2015	AttributeObject Recognition	—Unverified
Semi-Supervised Domain Adaptation With Subspace Learning for Visual Recognition	Jun 1, 2015	Domain AdaptationObject Recognition	—Unverified
Data-Driven 3D Voxel Patterns for Object Category Recognition	Jun 1, 2015	ObjectObject Recognition	—Unverified
A Dynamic Programming Approach for Fast and Robust Object Pose Recognition From Range Images	Jun 1, 2015	Object RecognitionPose Estimation	—Unverified
Is Object Localization for Free? - Weakly-Supervised Learning With Convolutional Neural Networks	Jun 1, 2015	General ClassificationObject	—Unverified
DeepContour: A Deep Convolutional Feature Learned by Positive-Sharing Loss for Contour Detection	Jun 1, 2015	Contour DetectionImage Segmentation	—Unverified
Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition	Jun 1, 2015	ObjectObject Recognition	—Unverified
CURL: Co-trained Unsupervised Representation Learning for Image Classification	May 29, 2015	ClassificationGeneral Classification	—Unverified
Texture Synthesis Using Convolutional Neural Networks	May 27, 2015	ObjectObject Recognition	CodeCode Available
The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition	May 17, 2015	Action RecognitionMulti-class Classification	—Unverified
Robust Visual Knowledge Transfer via EDA	May 17, 2015	Domain AdaptationObject Recognition	—Unverified
Dense Semantic Correspondence where Every Pixel is a Classifier	May 15, 2015	Object RecognitionSemantic correspondence	—Unverified
PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Edge-Preserving Coherence	May 13, 2015	Image SegmentationObject Recognition	—Unverified
Sparse 3D convolutional neural networks	May 12, 2015	3D Object RecognitionObject Recognition	CodeCode Available
Improving neural networks with bunches of neurons modeled by Kumaraswamy units: Preliminary study	May 11, 2015	Object Recognitionspeech-recognition	—Unverified

Show:10 25 50

← PrevPage 73 of 82Next →

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