activity
20232025
most cited3D-VisTA: Pre-trained Transformer for 3D Vision and Text Alignment

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SI2025

Efficient Integration of Multi-View Attributed Graphs for Clustering and Embedding

Yiran Li, Gongyao Guo, Jieming Shi +2

A multi-view attributed graph (MVAG) G captures the diverse relationships and properties of real-world entities through multiple graph views and attribute views. Effectively utiliz…

cs.CV2025

MetaScenes: Towards Automated Replica Creation for Real-world 3D Scans

Huangyue Yu, Baoxiong Jia, Yixin Chen +9

Embodied AI (EAI) research requires high-quality, diverse 3D scenes to effectively support skill acquisition, sim-to-real transfer, and generalization. Achieving these quality stan…

cs.CV2025

Unveiling the Mist over 3D Vision-Language Understanding: Object-centric Evaluation with Chain-of-Analysis

Jiangyong Huang, Baoxiong Jia, Yan Wang +5

Existing 3D vision-language (3D-VL) benchmarks fall short in evaluating 3D-VL models, creating a "mist" that obscures rigorous insights into model capabilities and 3D-VL tasks. Thi…

cs.CL2024

Reasoning Factual Knowledge in Structured Data with Large Language Models

Sirui Huang, Yanggan Gu, Xuming Hu +3

Large language models (LLMs) have made remarkable progress in various natural language processing tasks as a benefit of their capability to comprehend and reason with factual knowl…

cs.CV20231 cited

3D-VisTA: Pre-trained Transformer for 3D Vision and Text Alignment

Ziyu Zhu, Xiaojian Ma, Yixin Chen +3

3D vision-language grounding (3D-VL) is an emerging field that aims to connect the 3D physical world with natural language, which is crucial for achieving embodied intelligence. Cu…