CARA: Collision-Aware Resolution Adaptation for Multiresolution Hash Encoding Based Image Fitting
Multiresolution hash encodings have recently enabled fast and high-fidelity implicit neural representations by storing multi-scale features in fixed-size hash tables along a geometric resolution schedule. However, the standard design is data-agnostic: different resolution levels receive identical hash-table capacity despite large differences in image frequency content. As a result, some levels experience severe hash collisions while others underutilize parameters, leading to inefficient capacity allocation. To address this issue, we propose Collision-Aware Resolution Adaptation (CARA), a method that assigns per-level resolutions by balancing the effective information load across hash leve...
| Authors | Linfeng Ye, Zhixiang Chi, Shayan Mohajer Hamidi et al. |
|---|---|
| Primary category | cs.CV |
| Published | 16 September 2026 |
| Last updated at source | 16 September 2026 |
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