Hugging Face Trending Papers

ReRef-3D: A Benchmark for Spatial Referring Expression-Guided 3D Scene Rearrangement

Read the original on Hugging Face Trending Papers →

We introduce ReRef-3D, a benchmark for language-guided placement in 3D scenes. It contains 33,826 instructions across 998 CLEVR-derived scenes, spanning 16 placement families and direct, one-hop, and two-hop references.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at Hugging Face Trending Papers.

arXiv Computer Vision
Oct 22

VoxProg: 3D Spatial Reasoning through Voxel Programming

VoxProg introduces voxel programming for 3D spatial reasoning, enabling language models to translate task interpretations into executable programs that operate on local voxel views of scene surfaces. By indexing surface geometry on regular grids, the approach isolates task-relevant regions and boundaries, allowing downstream pose programs to compute target SE(3) poses. The method is evaluated on the 71-task VoxProg-Bench benchmark, showing consistent superiority over relation-based, keypoint-based, and mesh-based baselines.

By Zhichao Zhai, Menglei Zhao, Guikun Chen, Zihao Yan, Kanzhi Wu, Wenguan Wang, Jun Xiao
arXiv Computation and Language
Sep 2

Apples on the Table? Evaluating Text-Guided 3D Scene Synthesis via Fine-Grained Constraint Verification

The paper introduces LEGO, a benchmark dataset pairing user text descriptions with human‑annotated fine‑grained constraints and reference 3D scenes, and LEGO‑Eval, an evaluation framework that decomposes descriptions into atomic constraints and verifies each using grounding and spatial reasoning tools. It demonstrates that LEGO‑Eval detects misalignment more accurately than existing methods and that current 3D scene synthesis approaches achieve at most a 10% success rate on this benchmark.

By Minseok Kang, Dongwook Choi, Gyeom Hwangbo, Seungwon Lim, Kai Tzu-iunn Ong, Jinyoung Yeo