Hongshuo Tian

Orcid: 0000-0001-7635-0961

According to our database1, Hongshuo Tian authored at least 15 papers between 2020 and 2024.

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

Timeline

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Bibliography

2024
Multi-Modal Validation and Domain Interaction Learning for Knowledge-Based Visual Question Answering.
IEEE Trans. Knowl. Data Eng., November, 2024

Learning to Supervise Knowledge Retrieval Over a Tree Structure for Visual Question Answering.
IEEE Trans. Multim., 2024

Event-Aware Retrospective Learning for Knowledge-Based Image Captioning.
IEEE Trans. Multim., 2024

Counterfactual Visual Dialog: Robust Commonsense Knowledge Learning From Unbiased Training.
IEEE Trans. Multim., 2024

How to Understand Named Entities: Using Common Sense for News Captioning.
CoRR, 2024

Rule-driven News Captioning.
CoRR, 2024

Cross-Modal Coherence-Enhanced Feedback Prompting for News Captioning.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

CAT-DM: Controllable Accelerated Virtual Try-On with Diffusion Model.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Causality is all you need.
CoRR, 2023

Knowledge Prompt Makes Composed Pre-Trained Models Zero-Shot News Captioner.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Towards Confidence-Aware Commonsense Knowledge Integration for Scene Graph Generation.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

2022
Toward Region-Aware Attention Learning for Scene Graph Generation.
IEEE Trans. Neural Networks Learn. Syst., 2022

2021
Coupled-dynamic learning for vision and language: Exploring Interaction between different tasks.
Pattern Recognit., 2021

Mask and Predict: Multi-step Reasoning for Scene Graph Generation.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

2020
Part-Aware Interactive Learning for Scene Graph Generation.
Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020


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