HyperAI
HomeNewsLatest PapersTutorialsDatasetsWikiSOTALLM ModelsGPU LeaderboardEvents
Search
About
HyperAI

Image To Text Retrieval On Coco

Metrics

Recall@1
Recall@10
Recall@5

Results

Performance results of various models on this benchmark

Model Name
Recall@1
Recall@10
Recall@5
Paper TitleRepository
BLIP-2 (ViT-L, fine-tuned)83.598.096.0BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
BLIP-2 (ViT-G, fine-tuned)85.498.597.0BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
DVSA-74.8-Deep Visual-Semantic Alignments for Generating Image Descriptions
ONE-PEACE (ViT-G, w/o ranking)84.198.396.3ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities
Unicoder-VL-97.2-Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training-
SigLIP (ViT-L, zero-shot)70.6--Sigmoid Loss for Language Image Pre-Training
Oscar-99.8-Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
FLAVA (ViT-B, zero-shot)42.74-76.76FLAVA: A Foundational Language And Vision Alignment Model
IAIS67.7894.4889.7Learning Relation Alignment for Calibrated Cross-modal Retrieval
CLIP (zero-shot)58.488.181.5Learning Transferable Visual Models From Natural Language Supervision
0 of 10 row(s) selected.