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cs.CV2025
Differentiable Hierarchical Visual Tokenization
Marius Aasan, Martine Hjelkrem-Tan, Nico Catalano +2
Vision Transformers rely on fixed patch tokens that ignore the spatial and semantic structure of images. In this work, we introduce an end-to-end differentiable tokenizer that adap…
cs.CV2025
SPoT: Subpixel Placement of Tokens in Vision Transformers
Martine Hjelkrem-Tan, Marius Aasan, Gabriel Y. Arteaga +1
Vision Transformers naturally accommodate sparsity, yet standard tokenization methods confine features to discrete patch grids. This constraint prevents models from fully exploitin…