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SpaceFlow: Locally Controllable 3D Generation

Paper recorded by Signals 4 on 2026-10-08 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-08 on arXiv · recorded by Signals 4 on 2026-10-09

Category: cs.AI · 人工智能 · first seen 2026-10-09

Abstract

Current 3D generation methods lack explicit local control: geometric adherence is often defined by a global control strength, and appearance cannot be specified locally. We present SpaceFlow, a training-free pipeline for locally controllable 3D generation from text descriptions and a collection of geometric primitives. Each primitive serves as a proxy for an object part and is assigned a local con

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#372 most recent of 960 cs.AI papers we have recorded · ↑ newer: LeWAM: A JEPA World Action Model with Diffusion-Steering-Based MPC · ↓ older: HRIL: Learning Multimodal Synergy via Higher-Order Tensor Modeling
Cite this page: SpaceFlow: Locally Controllable 3D Generation: the #372 most recent of 960 cs.AI papers we have recorded (as of 2026-10-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/spaceflow-locally-controllable-3d-generation.html
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