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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
Published:
This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false. Read more
Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool. Read more
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool. Read more
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool. Read more
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool. Read more
portfolio
publications
Distribution-aware Low-bit Quantization for 3D Point Cloud Networks
Published in 2022 IEEE International Conference on Visual Communications and Image Processing (VCIP), 2022
Various low-bit quantized methods have been widely exploited and shown decent performance on 2D vision tasks in recent years. Complemented with 2D images, 3D point clouds provide an opportunity to understand the surrounding environ-ment better. However, low-bit quantization methods designed for 2D vision tasks are not readily transferable to 3D point clouds due to the higher dimension of 3D data and the increased proportion of activations. … Read more
Recommended citation:
Hu, D., Chen, S., Yang, H., & Wang, G. (2022, December). Distribution-aware Low-bit Quantization for 3D Point Cloud Networks. In 2022 IEEE International Conference on Visual Communications and Image Processing (VCIP) (pp. 1-5). IEEE. [pdf] [bib]
Efficient Heatmap-Guided 6-Dof Grasp Detection in Cluttered Scenes
Published in IEEE Robotics and Automation Letters, 2023
Fast and robust object grasping in clutter is a crucial component of robotics. Most current works resort to the whole observed point cloud for 6-Dof grasp generation, ignoring the guidance information excavated from global semantics, thus limiting high-quality grasp generation and real-time performance. … Read more
Recommended citation:
Chen, S., Tang, W., Xie, P., Yang, W., & Wang, G. (2023). Efficient heatmap-guided 6-DoF grasp detection in cluttered scenes. IEEE Robotics and Automation Letters. [pdf] [bib]
Part-Guided 3D RL for Sim2Real Articulated Object Manipulation
Published in IEEE Robotics and Automation Letters, 2023
Manipulating unseen articulated objects through visual feedback is a critical but challenging task for real robots. Existing learning-based solutions mainly focus on visual affordance learning or other pre-trained visual models to guide manipulation policies, which face challenges for novel instances in real-world scenarios. … Read more
Recommended citation:
Xie, P., Chen, R., Chen, S., Qin, Y., Xiang, F., Sun, T., ... & Su, H. (2023). Part-Guided 3D RL for Sim2Real Articulated Object Manipulation. IEEE Robotics and Automation Letters. [pdf] [bib]
Query-guided Support Prototypes for Few-shot 3D Indoor Segmentation
Published in IEEE Transactions on Circuits and Systems for Video Technology, 2023
Few-shot 3D point cloud segmentation segments novel categories in point cloud scenes with only limited annotations. However, most current methods do not consider query content when exploring support prototypes, and thus suffer from intra-class variations between objects and incomplete representation of category information from annotated support samples. … Read more
Recommended citation:
Hu, D., Chen, S., Yang, H., & Wang, G. (2023). Query-guided Support Prototypes for Few-shot 3D Indoor Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. [pdf] [bib]
Uncertainty-Aware Laser Stripe Segmentation with Non-Local Mechanisms for Welding Robots
Published in under review, 2024
The line-structured-light system has been widely applied in intelligent welding robots for weld seam reconstruction and tracking. However, it’s challenging to extract the projected laser stripes from captured images due to the strong noise and high dynamic range in welding environments. … Read more
Recommended citation: Yixiang Dai, Siang Chen, Tianyu Sun, Zimo Fan, Chun Zhang, Xiaobing Feng, Guijin Wang. (2024). Uncertainty-Aware Laser Stripe Segmentation with Non-Local Mechanisms for Welding Robots.
Rethinking 6-Dof Grasp Detection: A Flexible Framework for High-Quality Grasping
Published in arXiv preprint, 2024
Robotic grasping is a primitive skill for complex tasks and is fundamental to intelligence. For general 6-Dof grasping, most previous methods directly extract scene-level semantic or geometric information, while few of them consider the suitability for various downstream applications, such as target-oriented grasping. … Read more
Recommended citation:
Pengwei Xie, Siang Chen, Wei Tang, Dingchang Hu, Wenming Yang, Guijin Wang. (2024). Rethinking 6-Dof Grasp Detection: A Flexible Framework for High-Quality Grasping. arXiv preprint arXiv:2403.15054. [pdf]
Region-Centric 6-Dof Grasp Detection: A Data-Efficient Solution for Cluttered Scenes
Published in under revision, 2024
Robotic grasping, serving as the cornerstone for complex manipulation tasks, is fundamental for embodied intelligence. For general 6-Dof grasping, most data-driven methods directly extract scene-level information, resorting to fitting with a large amount of data. … Read more
Recommended citation: Wei Tang, Siang Chen, Pengwei Xie, Dingchang Hu, Wenming Yang, Guijin Wang. (2024). Region-Centric 6-Dof Grasp Detection: A Data-Efficient Solution for Cluttered Scenes.
Category-Agnostic Pose Estimation for Point Clouds
Published in IEEE International Conference on Image Processing 2024 (ICIP 2024), 2024
The goal of object pose estimation is to visually determine the pose of a specific object in the RGB-D input. Unfortunately, when faced with new categories, both instance-based and category-based methods are unable to deal with unseen objects of unseen categories, which is a challenge for pose estimation. … Read more
Recommended citation:
Bowen Liu, Wei Liu, Siang Chen, Pengwei Xie, Guijin Wang. (2024). Category-Agnostic Pose Estimation for Point Clouds. [pdf]
Variation-robust Few-shot 3D Affordance Segmentation for Robotic Manipulation
Published in under review, 2024
Traditional affordance segmentation on 3D point cloud objects requires massive amounts of annotated training data and can only make predictions within predefined classes and affordance tasks. … Read more
Recommended citation: Dingchang Hu, Tianyu Sun, Pengwei Xie, Siang Chen, Yixiang Dai, Huazhong Yang, Guijin Wang. (2024). Variation-robust Few-shot 3D Affordance Segmentation for Robotic Manipulation.
Target-Oriented Object Grasping via Multimodal Human Guidance
Published in ECCV 2024 Workshop on Assistive Computer Vision and Robotic (ACVR 2024), 2024
In the context of human-robot interaction and collaboration scenarios, robotic grasping still encounters numerous challenges. Traditional grasp detection methods generally analyze the entire scene to predict grasps, leading to redundancy and inefficiency. … Read more
Recommended citation:
Pengwei Xie, Siang Chen, Dingchang Hu, Yixiang Dai, Kaiqin Yang, Guijin Wang. (2024). Target-Oriented Object Grasping via Multimodal Human Guidance. [pdf]
Region-aware Grasp Framework with Normalized Grasp Space for Efficient 6-DoF Grasping
Published in CoRL 2024, 2024
A series of region-based methods succeed in extracting regional features and enhancing grasp detection quality. However, faced with a cluttered scene with potential collision, the definition of the grasp-relevant region stays inconsistent, and the relationship between grasps and regional spaces remains incompletely investigated. … Read more
Recommended citation:
Siang Chen, Pengwei Xie, Tang Wei, Dingchang Hu, Yixiang Dai, Guijin Wang. (2024). Region-aware Grasp Framework with Normalized Grasp Space for Efficient 6-DoF Grasping. [pdf]
GAP-RL: Grasps As Points for RL Towards Dynamic Object Grasping
Published in IEEE Robotics and Automation Letters, 2024
Dynamic grasping of moving objects in complex, continuous motion scenarios remains challenging. Reinforcement Learning (RL) has been applied in various robotic manipulation tasks, benefiting from its closed-loop property. … Read more
Recommended citation:
Pengwei Xie, Siang Chen, Qianrun Chen, Wei Tang, Dingchang Hu, Yixiang Dai, Rui Chen, Guijin Wang. (2024). GAP-RL: Grasps As Points for RL Towards Dynamic Object Grasping. [pdf]
talks
Oral presentation in ICRA2024
Published:
In May 2024, I gived presentation for our published paper Efficient heatmap-guided 6-DoF grasp detection in cluttered scenes in 2024 IEEE International Conference on Robotics and Automation (ICRA2024), Yokohama, Japan. I am quite excited for my first academic presentation in an international conference and hope to attend more conferences in the near future. Read more
teaching
Image Processing
Teaching Assistant in undergraduate course, Department of Electronic Engineering, Tsinghua University, 2022
Image engineering is a new interdisciplinary field that systematically studies various image theories, technologies, and applications. Its content can be divided into three layers: image processing, image analysis, and image understanding. This course is the first one in the image course, mainly introducing low-level content, with a certain depth and breadth. Through the study of this course, readers can solve some practical application problems of image technology on the one hand, and on the other hand, it will also lay a foundation for further learning of mid to high-level technologies in image engineering. Read more
Pattern Recognition
Teaching Assistant in postgraduate course, Department of Electronic Engineering, Tsinghua University, 2023
A course designed for non pattern recognition and intelligent systems majors. Taking rich application examples as the main thread, teach the basic concepts, methods, applications, limitations, and latest developments in modeling, training, classification, and clustering of statistics and structural pattern recognition. Read more
Management Assistant
Management Assistant Teaching Labs of Electronic Engineering Department, Department of Electronic Engineering, Tsinghua University, 2024
Assistant Manager of Teaching Labs of Electronic Engineering Department, Tsinghua University, responsible for the duty of the computer laboratory and maintenance of the servers. Read more