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 51–75 of 175 papers

TitleStatusHype
Instant Multi-View Head Capture through Learnable RegistrationCode1
CoHD: A Counting-Aware Hierarchical Decoding Framework for Generalized Referring Expression SegmentationCode1
Convolutional Hough Matching NetworksCode1
Multi-scale Matching Networks for Semantic CorrespondenceCode1
Multi-Compound Transformer for Accurate Biomedical Image SegmentationCode1
PPMN: Pixel-Phrase Matching Network for One-Stage Panoptic Narrative GroundingCode1
Correspondence Networks with Adaptive Neighbourhood ConsensusCode1
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph ConvolutionCode1
Feature-Robust Optimal Transport for High-Dimensional Data—0
Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objects—0
Bridging Viewpoint Gaps: Geometric Reasoning Boosts Semantic Correspondence—0
Eye-for-an-eye: Appearance Transfer with Semantic Correspondence in Diffusion Models—0
ASIC: Aligning Sparse in-the-wild Image Collections—0
Learning Semantic Correspondence Exploiting an Object-level Prior—0
Evaluating book summaries from internal knowledge in Large Language Models: a cross-model and semantic consistency approach—0
Joint Learning of Feature Extraction and Cost Aggregation for Semantic Correspondence—0
ContraReg: Contrastive Learning of Multi-modality Unsupervised Deformable Image Registration—0
BitSim: An Algebraic Similarity Measure for Description Logics Concepts—0
Learning Contrastive Representation for Semantic Correspondence—0
CONDA: Condensed Deep Association Learning for Co-Salient Object Detection—0
DreamMover: Leveraging the Prior of Diffusion Models for Image Interpolation with Large Motion—0
BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-based Video Colorization—0
Do It Yourself: Learning Semantic Correspondence from Pseudo-Labels—0
Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence—0
Learning From Noisy Correspondence With Tri-Partition for Cross-Modal Matching—0
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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