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 101–150 of 175 papers

TitleStatusHype
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
UltraMNIST Classification: A Benchmark to Train CNNs for Very Large Images—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
SPair-71k: A Large-scale Benchmark for Semantic Correspondence—0
MathBERT: A Pre-Trained Model for Mathematical Formula Understanding—0
MOSMOS: Multi-organ segmentation facilitated by medical report supervision—0
MotionRAG-Diff: A Retrieval-Augmented Diffusion Framework for Long-Term Music-to-Dance Generation—0
Structured Multi-modal Feature Embedding and Alignment for Image-Sentence Retrieval—0
Near-realtime Facial Animation by Deep 3D Simulation Super-Resolution—0
Syntactic Semantic Correspondence in Dependency Grammar—0
Object-Aware Dense Semantic Correspondence—0
Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification—0
OmniCreator: Self-Supervised Unified Generation with Universal Editing—0
OneSeg: Self-learning and One-shot Learning based Single-slice Annotation for 3D Medical Image Segmentation—0
Order embeddings and character-level convolutions for multimodal alignment—0
PARN: Pyramidal Affine Regression Networks for Dense Semantic Correspondence—0
Advanced Multimodal Deep Learning Architecture for Image-Text Matching—0
A Framework For Image Synthesis Using Supervised Contrastive Learning—0
Reference Based Color Transfer for Medical Volume Rendering—0
Bidirectional Retrieval Made Simple—0
BiSTNet: Semantic Image Prior Guided Bidirectional Temporal Feature Fusion for Deep Exemplar-based Video Colorization—0
BitSim: An Algebraic Similarity Measure for Description Logics Concepts—0
Bridging Viewpoint Gaps: Geometric Reasoning Boosts Semantic Correspondence—0
Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence—0
FCSS: Fully Convolutional Self-Similarity for Dense Semantic CorrespondenceCode0
Feature Robust Optimal Transport for High-dimensional DataCode0
Capturing Semantic Similarity for Entity Linking with Convolutional Neural NetworksCode0
CPGAN: Full-Spectrum Content-Parsing Generative Adversarial Networks for Text-to-Image SynthesisCode0
PatchMatch-Based Neighborhood Consensus for Semantic CorrespondenceCode0
TC-MGC: Text-Conditioned Multi-Grained Contrastive Learning for Text-Video RetrievalCode0
Lexical Sememe Prediction using Dictionary Definitions by Capturing Local Semantic CorrespondenceCode0
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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