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 31–40 of 2042 papers

Title	Date	Tasks	Status	Hype
Zoomer: Adaptive Image Focus Optimization for Black-box MLLM	Apr 30, 2025	Image CaptioningObject Recognition	—Unverified	0
LM-MCVT: A Lightweight Multi-modal Multi-view Convolutional-Vision Transformer Approach for 3D Object Recognition	Apr 27, 2025	3D Object RecognitionObject	—Unverified	0
Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency	Apr 24, 2025	BenchmarkingMath	CodeCode Available	1
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency	Apr 24, 2025	Autonomous NavigationDeep Learning	—Unverified	0
V^2R-Bench: Holistically Evaluating LVLM Robustness to Fundamental Visual Variations	Apr 23, 2025	Dataset GenerationObject Recognition	—Unverified	0
Naturally Computed Scale Invariance in the Residual Stream of ResNet18	Apr 22, 2025	Object Recognition	CodeCode Available	0
Quantum Doubly Stochastic Transformers	Apr 22, 2025	Inductive BiasObject Recognition	—Unverified	0
Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation	Apr 17, 2025	GPUObject Recognition	CodeCode Available	2
DVLTA-VQA: Decoupled Vision-Language Modeling with Text-Guided Adaptation for Blind Video Quality Assessment	Apr 16, 2025	Language ModelingLanguage Modelling	—Unverified	0
Visual Language Models show widespread visual deficits on neuropsychological tests	Apr 15, 2025	Object RecognitionVisual Reasoning	—Unverified	0

Show:10 25 50

← PrevPage 4 of 205Next →

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