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Object Counting On Fsc147

Métriques

MAE(test)

MAE(val)

RMSE(test)

RMSE(val)

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	MAE(test)	MAE(val)	RMSE(test)	RMSE(val)	Paper Title	Repository
GeCo	7.91	9.52	54.28	43.00	A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation	-
RCC	17.12	17.49	104.53	58.81	Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervision	-
SAFECount	14.32	15.28	85.54	47.20	Few-shot Object Counting with Similarity-Aware Feature Enhancement	-
Counting-DETR	16.79	-	123.56	-	Few-shot Object Counting and Detection	-
GCA-SUN	14.00	16.06	92.19	53.04	GCA-SUNet: A Gated Context-Aware Swin-UNet for Exemplar-Free Counting	-
CounTR	11.95	13.13	91.23	49.83	CounTR: Transformer-based Generalised Visual Counting	-
SemAug-SAFECount	12.74	12.59	89.90	44.95	Semantic Generative Augmentations for Few-Shot Counting	-
DAVE	8.66	8.91	32.36	28.08	DAVE -- A Detect-and-Verify Paradigm for Low-Shot Counting	-
Omnicount (Open vocabulary, multi-label, without training)	18.63	-	112	-	OmniCount: Multi-label Object Counting with Semantic-Geometric Priors	-
FamNet	22.08	23.75	99.54	69.07	Learning To Count Everything	-
CACViT	9.13	10.63	48.96	37.95	Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic Counting	-
SemAug-CounTR	11.32	12.31	77.50	41.65	Semantic Generative Augmentations for Few-Shot Counting	-
CountGD	5.74	7.1	24.09	26.08	CountGD: Multi-Modal Open-World Counting	-
LaoNet	15.78	17.11	97.15	56.81	Object Counting: You Only Need to Look at One	-
CounTX (uses text descriptions instead of visual exemplars)	15.88	17.10	106.29	65.61	Open-world Text-specified Object Counting	-
SSD	9.58	9.73	64.13	29.72	Learning Spatial Similarity Distribution for Few-shot Object Counting	-
SPDCN	13.51	14.59	96.80	49.97	Scale-Prior Deformable Convolution for Exemplar-Guided Class-Agnostic Counting
LOCA	10.79	10.24	56.97	32.56	A Low-Shot Object Counting Network With Iterative Prototype Adaptation	-
BMNet+	14.62	15.74	91.83	58.53	Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting	-

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Object Counting On Fsc147 | SOTA | HyperAI