Zeyu Shangguan

Orcid: 0000-0003-1435-6959

According to our database1, Zeyu Shangguan authored at least 18 papers between 2022 and 2026.

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Timeline

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Bibliography

2026
Cross-domain Few-shot Object Detection with Multi-modal Textual Enrichment.
Int. J. Comput. Vis., June, 2026

OFlow: Injecting Object-Aware Temporal Flow Matching for Robust Robotic Manipulation.
CoRR, April, 2026

Unsupervised few-shot learning with object-aware and attribute-consistent augmentation.
Pattern Recognit., 2026

AMPL: An adaptive meta-prompt learner for few-shot image classification.
Neural Networks, 2026

2025
SCOOP'D: Learning Mixed-Liquid-Solid Scooping via Sim2Real Generative Policy.
CoRR, October, 2025

Robot Learning from Any Images.
CoRR, September, 2025

ManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation.
CoRR, May, 2025

Cross-Domain Multi-Modal Few-Shot Object Detection via Rich Text.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

Sequential Multi-Object Grasping with One Dexterous Hand.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025

2024
Improved region proposal network for enhanced few-shot object detection.
Neural Networks, 2024

Online Pseudo-Label Unified Object Detection for Multiple Datasets Training.
CoRR, 2024

Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector.
Proceedings of the Computer Vision - ECCV 2024, 2024

Test-Time Linear Out-of-Distribution Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Decoupled DETR for Few-Shot Object Detection.
Proceedings of the Computer Vision - ACCV 2024, 2024

2023
Decoupled DETR For Few-shot Object Detection.
CoRR, 2023

Few-shot Object Detection with Refined Contrastive Learning.
Proceedings of the 35th IEEE International Conference on Tools with Artificial Intelligence, 2023

Identification of Novel Classes for Improving Few-Shot Object Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Distinctive Fire and Smoke Detection with Self-Similar.
CoRR, 2022


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