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Image Captioning On Nocaps Val Overall

Metrics

CIDEr
Pretrain (#images)
SPICE

Results

Performance results of various models on this benchmark

Paper Title
BLIP-2 ViT-G FlanT5 XL (zero-shot)121.61.1B15.8BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
BLIP-2 ViT-G OPT 6.7B (zero-shot)121.01.1B15.3BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
BLIP-2 ViT-G OPT 2.7B (zero-shot)119.71.1B15.4BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
LEMON_large113.4200M 15.0Scaling Up Vision-Language Pre-training for Image Captioning
BLIP_ViT-L 113.2129M14.8BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
SimVLM112.21.8B-SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
BLIP_CapFilt-L109.6129M14.7BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
OmniVL107.514M14.7OmniVL:One Foundation Model for Image-Language and Video-Language Tasks
VinVL 95.55.7M 13.5 VinVL: Revisiting Visual Representations in Vision-Language Models
Enc-Dec90.2-12.1Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
OSCAR80.9345M11.3Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
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Image Captioning On Nocaps Val Overall | SOTA | HyperAI