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 41–50 of 2042 papers

Title	Date	Tasks	Status	Hype
MASSeg : 2nd Technical Report for 4th PVUW MOSE Track	Apr 14, 2025	Data AugmentationObject	CodeCode Available	0
Hardware, Algorithms, and Applications of the Neuromorphic Vision Sensor: a Review	Apr 11, 2025	Object RecognitionOptical Flow Estimation	—Unverified	0
P2Object: Single Point Supervised Object Detection and Instance Segmentation	Apr 10, 2025	Instance SegmentationMultiple Instance Learning	CodeCode Available	2
D-Feat Occlusions: Diffusion Features for Robustness to Partial Visual Occlusions in Object Recognition	Apr 8, 2025	Image GenerationObject	—Unverified	0
Advancing Egocentric Video Question Answering with Multimodal Large Language Models	Apr 6, 2025	Object RecognitionQuestion Answering	—Unverified	0
ForcePose: A Deep Learning Approach for Force Calculation Based on Action Recognition Using MediaPipe Pose Estimation Combined with Object Detection	Mar 28, 2025	Action RecognitionHuman-Object Interaction Detection	—Unverified	0
Evaluating Multimodal Language Models as Visual Assistants for Visually Impaired Users	Mar 28, 2025	Object RecognitionReading Comprehension	—Unverified	0
Foveated Instance Segmentation	Mar 27, 2025	Instance SegmentationObject Recognition	CodeCode Available	0
DuckSegmentation: A segmentation model based on the AnYue Hemp Duck Dataset	Mar 27, 2025	Knowledge DistillationObject Recognition	—Unverified	0
Leveraging 3D Geometric Priors in 2D Rotation Symmetry Detection	Mar 26, 2025	Object RecognitionSymmetry Detection	—Unverified	0

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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