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Research questionHow can single-pass image captioning capture fine-grained visual details without multi-stage latency?Image captioning systems often produce fluent descriptions while omitting attributes, counts, textures, materials, and spatial relations. Recovering these details through multi-stage generation and verification can substantially increase inference latency.
AI
Computer Vision
Image & Video Processing
Inference Optimization
Machine Learning
Multimodal Models
Latest papersRecent research connected to this question, newest first.A Glance Is All You Need: Single-Pass Fine-Grained Image Captioning with SimLossThe source studies vision-language models for single-pass fine-grained image captioning. It evaluates differentiable and black-box embedding-based supervision against single-pass and multi-stage baselines using detail precision, recall, F1, and inference latency; the reported differentiable variant runs roughly 20 times faster than the multi-stage pipeline.research paper · Sep 1, 2026
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