6 citations · 17 across the 18 of their papers we have counts for
19 papers
Puffin-World: Scaling a Unified Multimodal Model with Native 3D World States
Kang Liao, Yihang Luo, Xiao-Ming Wu +7
We propose Puffin-World, a unified multimodal architecture that integrates physical understanding, spatial simulation, and 3D world generation and reconstruction without relying on…
HATS: A Human-Agent Teleoperation System for Multi-Arm Data Collection
Zesen Lin, Jian-Jian Jiang, Haoming Cen +3
Many real-world manipulation scenarios, such as handling complex collaborative tasks and dealing with large workspaces, require coordination of more than two robotic arms. Conseque…
Task Editing for Generalizable 3D Visuomotor Policy Learning
Jian-Jian Jiang, YiHan Yang, Lan Wei +6
3D visuomotor policies offer a promising direction for complex robotic manipulation, as depth maps and point clouds provide rich geometric information for spatial reasoning. Howeve…
VLANeXt Family: A Systematic Study of VLA Models from Core Recipes to Emerging Paradigms
Xiao-Ming Wu, Bin Fan, Kang Liao +6
Following the rise of large foundation models, Vision-Language-Action models (VLAs) emerged, leveraging strong visual and language understanding from Vision-Language Models for gen…
ProEdit: Inversion-based Editing From Prompts Done Right
Zhi Ouyang, Dian Zheng, Xiao-Ming Wu +4
Inversion-based visual editing provides an effective and training-free way to edit an image or a video based on user instructions. Existing methods typically inject source image in…
Decomposed Object Manipulation via Dual-Actor Policy
Bin Fan, Jian-Jian Jiang, Zhuohao Li +5
Object manipulation, which focuses on learning to perform tasks on similar parts across different types of objects, can be divided into an approaching stage and a manipulation stag…
Panorama Generation From NFoV Image Done Right
Dian Zheng, Cheng Zhang, Xiao-Ming Wu +4
Generating 360-degree panoramas from narrow field of view (NFoV) image is a promising computer vision task for Virtual Reality (VR) applications. Existing methods mostly assess the…
iManip: Skill-Incremental Learning for Robotic Manipulation
Zexin Zheng, Jia-Feng Cai, Xiao-Ming Wu +3
The development of a generalist agent with adaptive multiple manipulation skills has been a long-standing goal in the robotics community. In this paper, we explore a crucial task,…
Rethinking Bimanual Robotic Manipulation: Learning with Decoupled Interaction Framework
Jian-Jian Jiang, Xiao-Ming Wu, Yi-Xiang He +4
Bimanual robotic manipulation is an emerging and critical topic in the robotics community. Previous works primarily rely on integrated control models that take the perceptions and…
AffordDexGrasp: Open-set Language-guided Dexterous Grasp with Generalizable-Instructive Affordance
Yi-Lin Wei, Mu Lin, Yuhao Lin +4
Language-guided robot dexterous generation enables robots to grasp and manipulate objects based on human commands. However, previous data-driven methods are hard to understand inte…
Real-to-Sim Grasp: Rethinking the Gap between Simulation and Real World in Grasp Detection
Jia-Feng Cai, Zibo Chen, Xiao-Ming Wu +3
For 6-DoF grasp detection, simulated data is expandable to train more powerful model, but it faces the challenge of the large gap between simulation and real world. Previous works…
PixelFade: Privacy-preserving Person Re-identification with Noise-guided Progressive Replacement
Delong Zhang, Yi-Xing Peng, Xiao-Ming Wu +2
Online person re-identification services face privacy breaches from potential data leakage and recovery attacks, exposing cloud-stored images to malicious attackers and triggering…
An Economic Framework for 6-DoF Grasp Detection
Xiao-Ming Wu, Jia-Feng Cai, Jian-Jian Jiang +3
Robotic grasping in clutters is a fundamental task in robotic manipulation. In this work, we propose an economic framework for 6-DoF grasp detection, aiming to economize the resour…
Grasp as You Say: Language-guided Dexterous Grasp Generation
Yi-Lin Wei, Jian-Jian Jiang, Chengyi Xing +5
This paper explores a novel task "Dexterous Grasp as You Say" (DexGYS), enabling robots to perform dexterous grasping based on human commands expressed in natural language. However…
Dexterous Grasp Transformer
Guo-Hao Xu, Yi-Lin Wei, Dian Zheng +2
In this work, we propose a novel discriminative framework for dexterous grasp generation, named Dexterous Grasp TRansformer (DGTR), capable of predicting a diverse set of feasible…
Single-View Scene Point Cloud Human Grasp Generation
Yan-Kang Wang, Chengyi Xing, Yi-Lin Wei +2
In this work, we explore a novel task of generating human grasps based on single-view scene point clouds, which more accurately mirrors the typical real-world situation of observin…
Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model
Dian Zheng, Xiao-Ming Wu, Shuzhou Yang +3
Universal image restoration is a practical and potential computer vision task for real-world applications. The main challenge of this task is handling the different degradation dis…
DiffuVolume: Diffusion Model for Volume based Stereo Matching
Dian Zheng, Xiao-Ming Wu, Zuhao Liu +2
Stereo matching is a significant part in many computer vision tasks and driving-based applications. Recently cost volume-based methods have achieved great success benefiting from t…
Estimator Meets Equilibrium Perspective: A Rectified Straight Through Estimator for Binary Neural Networks Training
Xiao-Ming Wu, Dian Zheng, Zuhao Liu +1
Binarization of neural networks is a dominant paradigm in neural networks compression. The pioneering work BinaryConnect uses Straight Through Estimator (STE) to mimic the gradient…