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 1121–1130 of 2042 papers

Title	Date	Tasks	Status
KerCNNs: biologically inspired lateral connections for classification of corrupted images	Oct 18, 2019	ClassificationGeneral Classification	—Unverified
Encoder-Decoder based CNN and Fully Connected CRFs for Remote Sensed Image Segmentation	Oct 14, 2019	2D Semantic SegmentationDecoder	—Unverified
What's in my Room? Object Recognition on Indoor Panoramic Images	Oct 14, 2019	Instance SegmentationObject	—Unverified
Contour Sparse Representation with SDD Features for Object Recognition	Oct 13, 2019	ClusteringGesture Recognition	—Unverified
eCNN: A Block-Based and Highly-Parallel CNN Accelerator for Edge Inference	Oct 13, 2019	4kDenoising	—Unverified
Machine Learning and Big Scientific Data	Oct 12, 2019	BIG-bench Machine LearningDeep Learning	—Unverified
Rotation-invariant shipwreck recognition with forward-looking sonar	Oct 11, 2019	Object Recognition	—Unverified
Next integrated result modelling for stopping the text field recognition process in a video using a result model with per-character alternatives	Oct 9, 2019	ClusteringObject Recognition	CodeCode Available
Continual Learning in Neural Networks	Oct 7, 2019	Continual LearningObject Recognition	CodeCode Available
Learning Relationships for Multi-View 3D Object Recognition	Oct 1, 2019	3D Object RecognitionObject	—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