collaborators

8 papers

cs.RO2026

ImagineUAV: Aerial Vision-Language Navigation via World-Action Modeling and Kinodynamic Planning

Xuchen Liu, Jiawei Huang, Shihao Xia +3

Vision-language navigation (VLN) for UAVs demands grounding free-form instructions into 6-DoF flight under partial observability. While Vision-Language-Action (VLA) models excel at…

cs.CV2026

NTIRE 2026 3D Restoration and Reconstruction in Real-world Adverse Conditions: RealX3D Challenge Results

Shuhong Liu, Chenyu Bao, Ziteng Cui +103

This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to…

cs.CV2026

PLAF: Pixel-wise Language-Aligned Feature Extraction for Efficient 3D Scene Understanding

Junjie Wen, Junlin He, Fei Ma +1

Accurate open-vocabulary 3D scene understanding requires semantic representations that are both language-aligned and spatially precise at the pixel level, while remaining scalable…

cs.CV2025

Open3D-VQA: A Benchmark for Comprehensive Spatial Reasoning with Multimodal Large Language Model in Open Space

Weichen Zhang, Zile Zhou, Xin Zeng +7

Spatial reasoning is a fundamental capability of multimodal large language models (MLLMs), yet their performance in open aerial environments remains underexplored. In this work, we…

cs.RO2025

CityNavAgent: Aerial Vision-and-Language Navigation with Hierarchical Semantic Planning and Global Memory

Weichen Zhang, Chen Gao, Shiquan Yu +6

Aerial vision-and-language navigation (VLN), requiring drones to interpret natural language instructions and navigate complex urban environments, emerges as a critical embodied AI…

cs.AI2025

Embodied-R: Collaborative Framework for Activating Embodied Spatial Reasoning in Foundation Models via Reinforcement Learning

Baining Zhao, Ziyou Wang, Jianjie Fang +7

Humans can perceive and reason about spatial relationships from sequential visual observations, such as egocentric video streams. However, how pretrained models acquire such abilit…