11 citations · 20 across the 34 of their papers we have counts for
16 papers · 1 filter
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…
AlignBot: Aligning VLM-powered Customized Task Planning with User Reminders Through Fine-Tuning for Household Robots
Zhaxizhuoma Zhaxizhuoma, Pengan Chen, Ziniu Wu +7
This paper presents AlignBot, a novel framework designed to optimize VLM-powered customized task planning for household robots by effectively aligning with user reminders. In domes…
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…
LiveScene: Language Embedding Interactive Radiance Fields for Physical Scene Rendering and Control
Delin Qu, Qizhi Chen, Pingrui Zhang +5
This paper scales object-level reconstruction to complex scenes, advancing interactive scene reconstruction. We introduce two datasets, OmniSim and InterReal, featuring 28 scenes w…
Learning Manipulation by Predicting Interaction
Jia Zeng, Qingwen Bu, Bangjun Wang +12
Representation learning approaches for robotic manipulation have boomed in recent years. Due to the scarcity of in-domain robot data, prevailing methodologies tend to leverage larg…
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…
Any2Point: Empowering Any-modality Large Models for Efficient 3D Understanding
Yiwen Tang, Ray Zhang, Jiaming Liu +8
Large foundation models have recently emerged as a prominent focus of interest, attaining superior performance in widespread scenarios. Due to the scarcity of 3D data, many efforts…
HPL-ESS: Hybrid Pseudo-Labeling for Unsupervised Event-based Semantic Segmentation
Linglin Jing, Yiming Ding, Yunpeng Gao +7
Event-based semantic segmentation has gained popularity due to its capability to deal with scenarios under high-speed motion and extreme lighting conditions, which cannot be addres…