SOTAVerified

Phrase Grounding

Given an image and a corresponding caption, the Phrase Grounding task aims to ground each entity mentioned by a noun phrase in the caption to a region in the image.

Source: Phrase Grounding by Soft-Label Chain Conditional Random Field

Papers

Showing 1–25 of 88 papers

TitleStatusHype
GLIPv2: Unifying Localization and Vision-Language UnderstandingCode4
Towards Visual Grounding: A SurveyCode3
OmDet: Large-scale vision-language multi-dataset pre-training with multimodal detection networkCode3
MDETR - Modulated Detection for End-to-End Multi-Modal UnderstandingCode2
PG-Video-LLaVA: Pixel Grounding Large Video-Language ModelsCode2
DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and GroundingCode1
What is Where by Looking: Weakly-Supervised Open-World Phrase-Grounding without Text InputsCode1
Unsupervised Vision-Language Parsing: Seamlessly Bridging Visual Scene Graphs with Language Structures via Dependency RelationshipsCode1
PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language ModelsCode1
MDETR -- Modulated Detection for End-to-End Multi-Modal UnderstandingCode1
Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence ModelsCode1
An Open and Comprehensive Pipeline for Unified Object Grounding and DetectionCode1
A Survey on Interpretable Cross-modal ReasoningCode1
Coarse-to-Fine Vision-Language Pre-training with Fusion in the BackboneCode1
Enhancing Representation in Radiography-Reports Foundation Model: A Granular Alignment Algorithm Using Masked Contrastive LearningCode1
Learning Cross-modal Context Graph for Visual GroundingCode1
Contrastive Learning for Weakly Supervised Phrase GroundingCode1
Kosmos-2: Grounding Multimodal Large Language Models to the WorldCode1
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge DistillationCode1
MAF: Multimodal Alignment Framework for Weakly-Supervised Phrase GroundingCode1
Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding—0
Griffon v2: Advancing Multimodal Perception with High-Resolution Scaling and Visual-Language Co-Referring—0
ELVIS: Empowering Locality of Vision Language Pre-training with Intra-modal Similarity—0
Dynamic Conditional Networks for Few-Shot Learning—0
Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment—0
Show:102550
← PrevPage 1 of 4Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GLIPv2R@187.7—Unverified
2FIBER-BR@187.4—Unverified
3GLIPR@187.1—Unverified
4PEVLR@184.4—Unverified
5MDETR-ENB5R@184.3—Unverified
6DIGNR@178.73—Unverified
7LCMCGR@176.74—Unverified
8Soft-Label Chain CRF (SL-CCRF)R@174.69—Unverified
9DDPN (ResNet-101)R@173.3—Unverified
10VisualBERTR@171.33—Unverified
#ModelMetricClaimedVerifiedStatus
1GBS Ensemble + 12-in-1Pointing Game Accuracy85.9—Unverified
2GbS Ensemble MS-COCOPointing Game Accuracy75.6—Unverified
3COCO_ELMo_PNASNetPointing Game Accuracy69.19—Unverified
#ModelMetricClaimedVerifiedStatus
1Fiber-BR@187.1—Unverified
2PEVLR@184.1—Unverified
3VisualBERTR@170.4—Unverified
#ModelMetricClaimedVerifiedStatus
1VG_BiLSTM_VGGPointing Game Accuracy62.76—Unverified
2GbS Ensemble MS-COCOPointing Game Accuracy58.21—Unverified
3MCBAccuracy28.91—Unverified
#ModelMetricClaimedVerifiedStatus
1GbS VGPointing Game Accuracy55.91—Unverified
2VG_ELMo_PNASNetPointing Game Accuracy55.16—Unverified
3GbS Ensemble MS-COCOPointing Game Accuracy54.55—Unverified