الرئيسية الأخبار أحدث الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

Point Cloud Registration On Kitti Trained On

المقاييس

Success Rate

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	Success Rate	Paper Title	Repository
FCGF+PointDSC	96.76	PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency	-
GeoTransformer	67.93	GeoTransformer: Fast and Robust Point Cloud Registration with Geometric Transformer	-
YOHO-O	81.44	You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors	-
GeDi	98.92	Learning general and distinctive 3D local deep descriptors for point cloud registration	-
FCGF	24.19	Fully Convolutional Geometric Features
YOHO-C	82.16	You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors	-
SpinNet	81.44	SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration	-
D3Feat-pred	36.76	D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features	-
Greedy Grid Search	90.27	Challenging the Universal Representation of Deep Models for 3D Point Cloud Registration	-
FCGF+SC2-PCR	97.66	SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration	-
Exhaustive Grid Search	94.95	Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark
Predator	41.20	PREDATOR: Registration of 3D Point Clouds with Low Overlap	-
FPFH+PointDSC	94.05	PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency	-
DIP	93.51	Distinctive 3D local deep descriptors	-

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Point Cloud Registration On Kitti Trained On | SOTA | HyperAI