Subtoken Vision Transformer for Fine-grained Recognition
SubViT enhances fine-grained visual recognition by selectively increasing token resolution only in discriminative image patches. It uses Attention-based Token Subdivision (ATS) to represent important areas with multiple subtokens while keeping the original tokens for global context. A two-stage training strategy learns how to select these regions efficiently, resulting in better accuracy and reduced latency.