MEVL-STP: Multi-Encoder and Vision Language Model for Arbitrarily Shaped Scene Text Spotting

arXiv:2609.28857 · cs.CV · Submitted 2026-09-23 · Read on arXiv

cs.CV

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• Transformer — 13× in this paper · explained in 2 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Progressive Scale Expansion — 7× in this paper
• Ablation — 4× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Frozen Foundation Encoders — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Decoupling — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Vision-Language Model — 3× in this paper
• Ablation study — 2× in this paper · explained in 1 episode
• Distillation — 2× in this paper · explained in 2 episodes
• Feature Extraction — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Homogenization — 2× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Multilingual Text Spotting
• DNTextSpotter: Arbitrary-Shaped Scene Text Spotting via Improved Denoising Training
• LRANet++: Low-Rank Approximation Network for Accurate and Efficient Text Spotting
• Qwen2.5 Technical Report
• TextBlockV2: Towards Precise-Detection-Free Scene Text Spotting with Pre-trained Language Model
• EVA-CLIP: Improved Training Techniques for CLIP at Scale

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