PASCAL VOC 2007

PASCAL VOC 2007 is a dataset for image recognition. The twenty object classes that have been selected are:

Person: person Animal: bird, cat, cow, dog, horse, sheep Vehicle: aeroplane, bicycle, boat, bus, car, motorbike, train Indoor: bottle, chair, dining table, potted plant, sofa, tv/monitor

The dataset can be used for image classification and object detection tasks.

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Benchmarks

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Task	Dataset Variant	Best Model
Weakly Supervised Object Detection	PASCAL VOC 2007	wetectron
Object Detection	PASCAL VOC 2007	Cascade Eff-B7 NAS-FPN
Multi-Label Classification	PASCAL VOC 2007	Q2L-CvT
Object Counting	Pascal VOC 2007 count-test	Supervised Density Map
Multi-label Image Recognition with Partial Labels	PASCAL VOC 2007	DualCoOp+TaI-DPT
Real-Time Object Detection	PASCAL VOC 2007	YOLO
Robust Object Detection	PASCAL VOC 2007	Faster R-CNN with Stylized Training Data
Open World Object Detection	PASCAL VOC 2007	ORE
Semantic Segmentation	PASCAL VOC 2007	GALDNet
Image Classification	PASCAL VOC 2007	NNCLR
Unsupervised Semantic Segmentation with Language-image Pre-training	PASCAL VOC 2007	CLIPpy ViT-B
Unsupervised Object Localization	PASCAL VOC 2007	DeepCut
Unsupervised Object Detection	PASCAL VOC 2007	CutLER
Object Localization	PASCAL VOC 2007	DeepCut