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QuadTok: Quadtree Visual Tokenizer for Autoregressive Image Generation

Paper recorded by Signals 4 on 2026-10-07 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-07 on arXiv · recorded by Signals 4 on 2026-10-08

Category: cs.CV · 计算机视觉 · first seen 2026-10-08

Abstract

We introduce QuadTok, a novel framework for visual tokenization and autoregressive image generation. Compared to traditional approaches using 2D grids or 1D token sequences, we propose a hierarchical quadtree structure, bridging the gap between 2D spatial binding and 1D sequence-level flexibility. The QuadTok tokenizer dynamically allocates representational capacity to visually intricate areas whi

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#320 most recent of 756 cs.CV papers we have recorded · ↑ newer: Video-Conditioned Generative Joint 2D-3D Hand Motion Recovery · ↓ older: Insights from Autoresearch for Solar Panel Segmentation
Cite this page: QuadTok: Quadtree Visual Tokenizer for Autoregressive Image Generation: the #320 most recent of 756 cs.CV papers we have recorded (as of 2026-10-07). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/quadtok-quadtree-visual-tokenizer-for-autoregressive-image-generation.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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