11 citations · 36 across the 32 of their papers we have counts for
37 papers
MixVLA: Adaptive Mixing of Non-Invariant Information for Generalizable Vision-Language-Action Models
Pingrui Zhang, Yu Zhang, Pengyuan Wu +8
Vision-Language-Action (VLA) models have achieved remarkable advances in robotic manipulation, yet their zero-shot generalization under out-of-distribution (OOD) conditions remains…
WOLF: World Model Guided LiDAR Exploration with Predictive Frontiers
Yuyang Tian, Penghui Yang, Pengyuan Wu +7
LiDAR-based unmanned aerial vehicle (UAV) exploration builds maps by continually selecting where to observe next. However, decisions based on the measured map provide limited fores…
Q-GeoMem: Question-Guided Geometric Memory for Video Spatial Reasoning
Xianqiang Gao, Qizhi Chen, Delin Qu +5
Video spatial reasoning requires accumulating viewpoint-dependent evidence over time while retaining information useful to the question being asked. Existing spatial video-language…
Closed-Loop Action Chunks with Dynamic Corrections for Training-Free Diffusion Policy
Pengyuan Wu, Pingrui Zhang, Zhigang Wang +3
Diffusion-based policies have achieved remarkable results in robotic manipulation but often struggle to adapt rapidly in dynamic scenarios, leading to delayed responses or task fai…
Understanding Degradation with Vision Language Model
Guanzhou Lan, Chenyi Liao, Yuqi Yang +5
Understanding visual degradations is a critical yet challenging problem in computer vision. While recent Vision-Language Models (VLMs) excel at qualitative description, they often…
FastUMI-100K: Advancing Data-driven Robotic Manipulation with a Large-scale UMI-style Dataset
Kehui Liu, Zhongjie Jia, Yang Li +14
Data-driven robotic manipulation learning depends on large-scale, high-quality expert demonstration datasets. However, existing datasets, which primarily rely on human teleoperated…
Cross from Left to Right Brain: Adaptive Text Dreamer for Vision-and-Language Navigation
Pingrui Zhang, Yifei Su, Pengyuan Wu +7
Vision-and-Language Navigation (VLN) requires the agent to navigate by following natural instructions under partial observability, making it difficult to align perception with lang…
Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation
Yuanqi Yao, Siao Liu, Haoming Song +7
Building a lifelong robot that can effectively leverage prior knowledge for continuous skill acquisition remains significantly challenging. Despite the success of experience replay…
AerialVG: A Challenging Benchmark for Aerial Visual Grounding by Exploring Positional Relations
Junli Liu, Qizhi Chen, Zhigang Wang +6
Visual grounding (VG) aims to localize target objects in an image based on natural language descriptions. In this paper, we propose AerialVG, a new task focusing on visual groundin…
MoMa-Kitchen: A 100K+ Benchmark for Affordance-Grounded Last-Mile Navigation in Mobile Manipulation
Pingrui Zhang, Xianqiang Gao, Yuhan Wu +6
In mobile manipulation, navigation and manipulation are often treated as separate problems, resulting in a significant gap between merely approaching an object and engaging with it…
Openfly: A comprehensive platform for aerial vision-language navigation
Yunpeng Gao, Chenhui Li, Zhongrui You +20
Vision-Language Navigation (VLN) aims to guide agents by leveraging language instructions and visual cues, playing a pivotal role in embodied AI. Indoor VLN has been extensively st…
Exploring the Potential of Encoder-free Architectures in 3D LMMs
Yiwen Tang, Zoey Guo, Zhuhao Wang +8
Encoder-free architectures have been preliminarily explored in the 2D Large Multimodal Models (LMMs), yet it remains an open question whether they can be effectively applied to 3D…
SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model
Delin Qu, Haoming Song, Qizhi Chen +8
In this paper, we claim that spatial understanding is the keypoint in robot manipulation, and propose SpatialVLA to explore effective spatial representations for the robot foundati…
Night-to-Day Translation via Illumination Degradation Disentanglement
Guanzhou Lan, Yuqi Yang, Zhigang Wang +3
Night-to-Day translation (Night2Day) aims to achieve day-like vision for nighttime scenes. However, processing night images with complex degradations remains a significant challeng…
Open-Vocabulary Octree-Graph for 3D Scene Understanding
Zhigang Wang, Yifei Su, Chenhui Li +4
Open-vocabulary 3D scene understanding is indispensable for embodied agents. Recent works leverage pretrained vision-language models (VLMs) for object segmentation and project them…
Efficient Diffusion as Low Light Enhancer
Guanzhou Lan, Qianli Ma, Yuqi Yang +4
The computational burden of the iterative sampling process remains a major challenge in diffusion-based Low-Light Image Enhancement (LLIE). Current acceleration methods, whether tr…
Exploring Spatial Representation to Enhance LLM Reasoning in Aerial Vision-Language Navigation
Yunpeng Gao, Zhigang Wang, Pengfei Han +3
Aerial Vision-and-Language Navigation (VLN) is a novel task enabling Unmanned Aerial Vehicles (UAVs) to navigate in outdoor environments through natural language instructions and v…
FastUMI: A Scalable and Hardware-Independent Universal Manipulation Interface with Dataset
Zhaxizhuoma, Kehui Liu, Chuyue Guan +15
Real-world manipulation data involving robotic arms is crucial for developing generalist action policies, yet such data remains scarce since existing data collection methods are hi…
COHERENT: Collaboration of Heterogeneous Multi-Robot System with Large Language Models
Kehui Liu, Zixin Tang, Dong Wang +3
Leveraging the powerful reasoning capabilities of large language models (LLMs), recent LLM-based robot task planning methods yield promising results. However, they mainly focus on…
Depth Helps: Improving Pre-trained RGB-based Policy with Depth Information Injection
Xincheng Pang, Wenke Xia, Zhigang Wang +4
3D perception ability is crucial for generalizable robotic manipulation. While recent foundation models have made significant strides in perception and decision-making with RGB-bas…
Learning 2D Invariant Affordance Knowledge for 3D Affordance Grounding
Xianqiang Gao, Pingrui Zhang, Delin Qu +4
3D Object Affordance Grounding aims to predict the functional regions on a 3D object and has laid the foundation for a wide range of applications in robotics. Recent advances tackl…
Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration
Ziran Zhang, Yuhang Tang, Zhigang Wang +2
Infrared imaging and turbulence strength measurements are in widespread demand in many fields. This paper introduces a Physical Prior Guided Cooperative Learning (P2GCL) framework…
KOI: Accelerating Online Imitation Learning via Hybrid Key-state Guidance
Jingxian Lu, Wenke Xia, Dong Wang +4
Online Imitation Learning struggles with the gap between extensive online exploration space and limited expert trajectories, hindering efficient exploration due to inaccurate rewar…
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation
Junjie Zhang, Chenjia Bai, Haoran He +5
Acquiring a multi-task imitation policy in 3D manipulation poses challenges in terms of scene understanding and action prediction. Current methods employ both 3D representation and…