Xingyu Zeng

According to our database1, Xingyu Zeng authored at least 35 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
Causal Evaluation of Language Models.
CoRR, 2024

Gradient-based Visual Explanation for Transformer-based CLIP.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Industry Systems.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: EMNLP 2024, 2024

CLEAR: Can Language Models Really Understand Causal Graphs?
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems.
CoRR, 2023

To be or not to be? an exploration of continuously controllable prompt engineering.
CoRR, 2023

MeanAP-Guided Reinforced Active Learning for Object Detection.
CoRR, 2023

TPTU: Task Planning and Tool Usage of Large Language Model-based AI Agents.
CoRR, 2023

Explore the Power of Dropout on Few-shot Learning.
CoRR, 2023

An Effective Crop-Paste Pipeline for Few-shot Object Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Explore the Power of Synthetic Data on Few-shot Object Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

SeqCo-DETR: Sequence Consistency Training for Self-Supervised Object Detection with Transformers.
Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022
A Unified Framework with Meta-dropout for Few-shot Learning.
CoRR, 2022

Scale-Aware Spatio-Temporal Relation Learning for Video Anomaly Detection.
Proceedings of the Computer Vision - ECCV 2022, 2022

Three-stage Training Pipeline with Patch Random Drop for Few-shot Object Detection.
Proceedings of the Computer Vision - ACCV 2022, 2022

2020
Adapting Object Detectors with Conditional Domain Normalization.
Proceedings of the Computer Vision - ECCV 2020, 2020

Rethinking Pseudo-LiDAR Representation.
Proceedings of the Computer Vision - ECCV 2020, 2020

Monocular 3D Object Detection with Decoupled Structured Polygon Estimation and Height-Guided Depth Estimation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
GS3D: An Efficient 3D Object Detection Framework for Autonomous Driving.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
T-CNN: Tubelets With Convolutional Neural Networks for Object Detection From Videos.
IEEE Trans. Circuits Syst. Video Technol., 2018

Crafting GBD-Net for Object Detection.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Webshell Traffic Detection With Character-Level Features Based on Deep Learning.
IEEE Access, 2018

2017
Visual Importance and Distortion Guided Deep Image Quality Assessment Framework.
IEEE Trans. Multim., 2017

DeepID-Net: Object Detection with Deformable Part Based Convolutional Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2017

2016
Partial Occlusion Handling in Pedestrian Detection With a Deep Model.
IEEE Trans. Circuits Syst. Video Technol., 2016

Learning Mutual Visibility Relationship for Pedestrian Detection with a Deep Model.
Int. J. Comput. Vis., 2016

Gated Bi-directional CNN for Object Detection.
Proceedings of the Computer Vision - ECCV 2016, 2016

2015
Single-Pedestrian Detection Aided by Two-Pedestrian Detection.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

Window-Object Relationship Guided Representation Learning for Generic Object Detections.
CoRR, 2015

Learning Deep Representation with Large-Scale Attributes.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

DeepID-Net: Deformable deep convolutional neural networks for object detection.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014
DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection.
CoRR, 2014

Deep Learning of Scene-Specific Classifier for Pedestrian Detection.
Proceedings of the Computer Vision - ECCV 2014, 2014

2013
Multi-stage Contextual Deep Learning for Pedestrian Detection.
Proceedings of the IEEE International Conference on Computer Vision, 2013

Modeling Mutual Visibility Relationship in Pedestrian Detection.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013


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