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 1–25 of 175 papers

TitleStatusHype
RL from Physical Feedback: Aligning Large Motion Models with Humanoid Control—0
Jamais Vu: Exposing the Generalization Gap in Supervised Semantic Correspondence—0
Do It Yourself: Learning Semantic Correspondence from Pseudo-Labels—0
MotionRAG-Diff: A Retrieval-Augmented Diffusion Framework for Long-Term Music-to-Dance Generation—0
Cora: Correspondence-aware image editing using few step diffusionCode1
Semantic Correspondence: Unified Benchmarking and a Strong BaselineCode1
TC-MGC: Text-Conditioned Multi-Grained Contrastive Learning for Text-Video RetrievalCode0
SemAlign3D: Semantic Correspondence between RGB-Images through Aligning 3D Object-Class Representations—0
Semantix: An Energy Guided Sampler for Semantic Style Transfer—0
Evaluating book summaries from internal knowledge in Large Language Models: a cross-model and semantic consistency approach—0
FPGS: Feed-Forward Semantic-aware Photorealistic Style Transfer of Large-Scale Gaussian Splatting—0
Evaluation of Multilingual Image Captioning: How far can we get with CLIP models?Code0
Towards Affordance-Aware Articulation Synthesis for Rigged Objects—0
Seeing Sound: Assembling Sounds from Visuals for Audio-to-Image Generation—0
Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature SpaceCode0
Bridging Viewpoint Gaps: Geometric Reasoning Boosts Semantic Correspondence—0
Self-Supervised Spatial Correspondence Across Modalities—0
Manga Generation via Layout-controllable Diffusion—0
DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo—0
A Framework For Image Synthesis Using Supervised Contrastive Learning—0
CleanDIFT: Diffusion Features without NoiseCode2
Distillation of Diffusion Features for Semantic Correspondence—0
Multi-Level Correlation Network For Few-Shot Image ClassificationCode0
OmniCreator: Self-Supervised Unified Generation with Universal Editing—0
Integration of Contextual Descriptors in Ontology Alignment for Enrichment of Semantic Correspondence—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
7VATPCK92.3—Unverified
8VAT (ECCV)PCK92.3—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 [email protected]61.6—Unverified