activity
20212025
most citedTPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage

13 citations · 34 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2025

ZeroBP: Learning Position-Aware Correspondence for Zero-shot 6D Pose Estimation in Bin-Picking

Jianqiu Chen, Zikun Zhou, Xin Li +3

Bin-picking is a practical and challenging robotic manipulation task, where accurate 6D pose estimation plays a pivotal role. The workpieces in bin-picking are typically textureles…

cs.AI2023★ 7 cited

TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems

Yilun Kong, Jingqing Ruan, Yihong Chen +9

Large Language Models (LLMs) have demonstrated proficiency in addressing tasks that necessitate a combination of task planning and the usage of external tools that require a blend…

cs.AI2023★ 13 cited

TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage

Jingqing Ruan, Yihong Chen, Bin Zhang +8

With recent advancements in natural language processing, Large Language Models (LLMs) have emerged as powerful tools for various real-world applications. Despite their prowess, the…

cs.CV2023★ 1 cited

Balancing Logit Variation for Long-tailed Semantic Segmentation

Yuchao Wang, Jingjing Fei, Haochen Wang +5

Semantic segmentation usually suffers from a long-tail data distribution. Due to the imbalanced number of samples across categories, the features of those tail classes may get sque…

cs.CV2023★ 4 cited

ZeroPose: CAD-Prompted Zero-shot Object 6D Pose Estimation in Cluttered Scenes

Jianqiu Chen, Zikun Zhou, Mingshan Sun +4

Many robotics and industry applications have a high demand for the capability to estimate the 6D pose of novel objects from the cluttered scene. However, existing classic pose esti…

cs.CV2023

SeqCo-DETR: Sequence Consistency Training for Self-Supervised Object Detection with Transformers

Guoqiang Jin, Fan Yang, Mingshan Sun +7

Self-supervised pre-training and transformer-based networks have significantly improved the performance of object detection. However, most of the current self-supervised object det…

cs.CV2022★ 2 cited

MIAD: A Maintenance Inspection Dataset for Unsupervised Anomaly Detection

Tianpeng Bao, Jiadong Chen, Wei Li +5

Visual anomaly detection plays a crucial role in not only manufacturing inspection to find defects of products during manufacturing processes, but also maintenance inspection to ke…

cs.CV2022

Geo6D: Geometric Constraints Learning for 6D Pose Estimation

Jianqiu Chen, Mingshan Sun, Ye Zheng +7

Numerous 6D pose estimation methods have been proposed that employ end-to-end regression to directly estimate the target pose parameters. Since the visible features of objects are…

cs.CV2022★ 1 cited

Uni6Dv2: Noise Elimination for 6D Pose Estimation

Mingshan Sun, Ye Zheng, Tianpeng Bao +5

Uni6D is the first 6D pose estimation approach to employ a unified backbone network to extract features from both RGB and depth images. We discover that the principal reasons of Un…

cs.CV2021★ 6 cited

Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization

Ye Zheng, Xiang Wang, Rui Deng +3

The essence of unsupervised anomaly detection is to learn the compact distribution of normal samples and detect outliers as anomalies in testing. Meanwhile, the anomalies in real-w…