不用打药也能生成增强脑MRI？解剖感知+频率引导的视觉Transformer，让对比增强影像合成更精准。
arXiv:2607.07553v1 Announce Type: new Abstract: Accurate tumour localization and diagnosis is a critical component of clinical care for brain cancers.…
视觉Transformer压缩新方案，多粒度随机自动剪枝兼顾精度与效率，模型轻量化研究值得一看。
arXiv:2603.12222v2 Announce Type: replace-cross Abstract: Vision Transformers require significant computational resources and memory bandwidth, severe…
最新ECCV 2026录用论文，探索如何对预训练视觉Transformer的表示进行可控操作，为视觉AI带来新的灵活性。
arXiv:2604.02327v2 Announce Type: replace Abstract: Pretrained Vision Transformers (ViTs) such as DINOv2 and MAE provide generic image features that c…
为视觉Transformer设计的新型忠实特征上采样方法，提升细节保留与精度。
arXiv:2606.14024v1 Announce Type: new Abstract: Vision Transformers (ViTs) have become a dominant architecture for visual representation learning, pro…
融合拓扑数据分析与视觉Transformer，在脑肿瘤四分类任务上取得新突破。
arXiv:2606.00927v1 Announce Type: new Abstract: Accurate brain tumor classification from magnetic resonance imaging (MRI) is a key requirement for ear…
提出测试时训练新范式，将Vision Transformer复杂度从二次降至线性，推理时仅需少量计算即可大幅提升准确率和鲁棒性。
arXiv:2605.02772v2 Announce Type: replace Abstract: While linear-complexity attention mechanisms offer a promising alternative to Softmax attention fo…
通过修改训练协议而非架构，让Vision Transformer更好地利用空间局部性，提升性能与效率。
arXiv:2605.16390v1 Announce Type: cross Abstract: We investigate whether the training protocol can induce spatial locality in the early layers of a Vi…