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20232026
most citedDriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model

18 citations · 18 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Lucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling

Minghan Qin, Yuang Wang, Xiuyu Yang +6

Composable scene modeling aims to recover a real indoor scene as complete, editable object assets arranged as observed, giving robot simulation and embodied AI a simulation-ready r…

cs.CV2026

Utonia: Toward One Encoder for All Point Clouds

Yujia Zhang, Xiaoyang Wu, Yunhan Yang +6

We dream of a future where point clouds from all domains can come together to shape a single model that benefits them all. Toward this goal, we present Utonia, a first step toward…

cs.CV2026

Any3D-VLA: Enhancing VLA Robustness via Diverse Point Clouds

Xianzhe Fan, Shengliang Deng, Xiaoyang Wu +7

Existing Vision-Language-Action (VLA) models typically take 2D images as visual input, which limits their spatial understanding in complex scenes. How can we incorporate 3D informa…

cs.CV2025

OmniPerson: Unified Identity-Preserving Pedestrian Generation

Changxiao Ma, Chao Yuan, Xincheng Shi +6

Person re-identification (ReID) suffers from a lack of large-scale high-quality training data due to challenges in data privacy and annotation costs. While previous approaches have…

cs.CV2025

Concerto: Joint 2D-3D Self-Supervised Learning Emerges Spatial Representations

Yujia Zhang, Xiaoyang Wu, Yixing Lao +4

Humans learn abstract concepts through multisensory synergy, and once formed, such representations can often be recalled from a single modality. Inspired by this principle, we intr…

cs.CV2023★ 18 cited

DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model

Zhenhua Xu, Yujia Zhang, Enze Xie +5

Multimodal large language models (MLLMs) have emerged as a prominent area of interest within the research community, given their proficiency in handling and reasoning with non-text…