SOTAVerified

Semantic correspondence

The task of semantic correspondence aims to establish reliable visual correspondence between different instances of the same object category.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 175 papers

TitleStatusHype
GPT-4o: Visual perception performance of multimodal large language models in piglet activity understanding—0
GS-Pose: Category-Level Object Pose Estimation via Geometric and Semantic Correspondence—0
Guided Semantic Flow—0
Semi-Supervised Learning of Semantic Correspondence with Pseudo-Labels—0
SFNet: Learning Object-aware Semantic Correspondence—0
Hierarchical Dense Correlation Distillation for Few-Shot Segmentation-Extended Abstract—0
Hierarchical Semantic Correspondence Learning for Post-Discharge Patient Mortality Prediction—0
Improving Semantic Correspondence with Viewpoint-Guided Spherical Maps—0
Independently Keypoint Learning for Small Object Semantic Correspondence—0
Integration of Contextual Descriptors in Ontology Alignment for Enrichment of Semantic Correspondence—0
Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence—0
Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence—0
Joint Learning of Feature Extraction and Cost Aggregation for Semantic Correspondence—0
Learning Contrastive Representation for Semantic Correspondence—0
Learning From Noisy Correspondence With Tri-Partition for Cross-Modal Matching—0
Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects—0
SimSC: A Simple Framework for Semantic Correspondence with Temperature Learning—0
Learning Semantic Correspondence Exploiting an Object-level Prior—0
SketchDesc: Learning Local Sketch Descriptors for Multi-view Correspondence—0
Learning SO(3)-Invariant Semantic Correspondence via Local Shape Transform—0
Learning Space-Time Semantic Correspondences—0
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation—0
Learning to Embed Semantic Correspondence for Natural Language Understanding—0
Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery—0
Manga Generation via Layout-controllable Diffusion—0
Show:102550
← PrevPage 4 of 4Next →
All datasetsSPair-71kPF-PASCALPF-WILLOWCaltech-101AP-10KCUB-200-2011

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GeoAware-SC (Supervised, AP-10K P.T.)PCK85.6—Unverified
2DINOv2PCK85.2—Unverified
3GeoAware-SC (Supervised)PCK82.9—Unverified
4SD+DINO (Supervised)PCK74.6—Unverified
5GeoAware-SC + CleanDIFT (Zero-Shot)PCK70—Unverified
6GeoAware-SC (Zero-Shot)PCK68.5—Unverified
7SD+DINO + CleanDIFT (Zero-Shot)PCK64.8—Unverified
8IFCATPCK64.4—Unverified
9SD+DINO (Zero-shot)PCK64—Unverified
10DIFT + CleanDIFT (Zero-Shot)PCK61.4—Unverified
#ModelMetricClaimedVerifiedStatus
1DINOv2PCK95.8—Unverified
2GeoAware-SC (Supervised, AP-10K P.T.)PCK95.7—Unverified
3GeoAware-SC (Supervised)PCK95.1—Unverified
4CATs++PCK93.8—Unverified
5SD+DINO (Supervised)PCK93.6—Unverified
6CATsPCK92.6—Unverified
7VAT (ECCV)PCK92.3—Unverified
8VATPCK92.3—Unverified
9CHMPCK91.6—Unverified
10DHPFPCK90.7—Unverified
#ModelMetricClaimedVerifiedStatus
1LDMCorrespondencesPCK84.3—Unverified
2VAT (ECCV)PCK81.6—Unverified
3VATPCK81—Unverified
4CHMPCK79.4—Unverified
5CATsPCK79.2—Unverified
6SCOTPCK78.1—Unverified
7DHPFPCK77.6—Unverified
8HPFPCK76.3—Unverified
#ModelMetricClaimedVerifiedStatus
1HPFIoU63—Unverified
2DHPFIoU62—Unverified
#ModelMetricClaimedVerifiedStatus
1DINOv2PCK87.4—Unverified
#ModelMetricClaimedVerifiedStatus
1LDM CorrespondencesMean PCK@0.0561.6—Unverified