HyperAI초신경

홈 뉴스 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

한국어

HyperAI초신경

Semantic Correspondence On Pf Pascal

평가 지표

PCK

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	PCK	Paper Title	Repository
HPF	88.3	Hyperpixel Flow: Semantic Correspondence with Multi-layer Neural Features
CHM	91.6	Convolutional Hough Matching Networks
SD+DINO (Supervised)	93.6	A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
VAT	92.3	Cost Aggregation Is All You Need for Few-Shot Segmentation
DHPF	90.7	Learning to Compose Hypercolumns for Visual Correspondence
CATs++	93.8	CATs++: Boosting Cost Aggregation with Convolutions and Transformers
SCOT	88.8	Semantic Correspondence as an Optimal Transport Problem	-
NC-Net	-	Neighbourhood Consensus Networks
GeoAware-SC (Supervised)	95.1	Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence
GeoAware-SC (Zero-Shot)	82.6	Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence
VAT (ECCV)	92.3	Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation
GeoAware-SC (Supervised, AP-10K P.T.)	95.7	Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence
CATs	92.6	CATs: Cost Aggregation Transformers for Visual Correspondence
ANCNet	88.7	Correspondence Networks with Adaptive Neighbourhood Consensus

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