I am a Deputy Reseacher(equal to Associate Professor) at School of Information and Software Engineering, UESTC. Before working at UESTC, I was a research fellow at Monash Univeristy. I earned my Ph.D. at Monash University in 2022 under the supervision of Assoc. Prof. Yuan-Fang Li and co-supervision with Prof. Lianli Gao. I obtained my MS and BS degrees in Computer Science from UESTC under the supervision of Prof. Jingkuan Song in 2018, and Northeast Normal University (NENU) in 2015, respectively. My research interests focus on computer vision, such as scene graph generation, human-object interaction detection, and image retrieval, etc.

Recent News

• One paper accepted to TIP 2023 on scene graph generation
• One paper accepted to TIP 2022 on unbiased scene graph generation
• One paper accepted to ECCV 2022 on open-vocabulary scene graph generation
• Starting my postdoc in the Vision and Language group from Feb. 2022.
• One paper accepted to TNNLS 2021 on network embedding
• One paper accepted to ICCV 2021 on Human-Ojbect interaction with scene graphs.
• One paper acccepted to IJCAI 2021 on scene graph generation.
• One paper accepted to AAAI 2020 on network quantisation.

Publications

• Tao He, Lianli Gao, Jingkuan Song, Yuan-Fang Li. Towards a Unified Transformer-based Framework for Scene Graph Generation and Human-object Interaction Detection. TIP 2023. [code] [paper]  
• Tao He, Lianli Gao, Jingkuan Song, Yuan-Fang Li. State-aware Compositional Learning towards Unbiased Training for Scene Graph Generation. TIP 2022. [code] [paper]  
• Tao He, Lianli Gao, Jingkuan Song, Yuan-Fang Li. Towards Open-vocabulary Scene Graph Generation with Prompt-based Finetuning. ECCV 2022. [code] [paper]  
• Tao He, Lianli Gao, Jingkuan Song, Yuan-Fang Li. Exploiting Scene Graphs for Human-Object Interaction Detection. ICCV 2021.[code] [paper]  
• Tao He, Lianli Gao, Jingkuan Song, Yuan-Fang Li.Semisupervised Network Embedding With Differentiable Deep Quantization. TNNLS 2021. [code] [paper]  
• Jingkuan Song, Tao He, Lianli Gao, Alan Hanjalic, Hengtao Shen. Unified Binary Generative Adversarial Network for Image Retrieval and Compression. IJCV 2020.[code] [paper]  
• Tao He, Lianli Gao, Jingkuan Song, Xing Wang, Ke Huang, Yuan-Fang Li. Sneq: Semi-supervised Attributed Network Embedding with Attention-based Quantisation. AAAI 2020.[code] [paper]  
• Tao He, Lianli Gao, Jingkuan Song, Jianfei Cai, Yuan-Fang Li. Learning from the scene and borrowing from the rich: Tackling the long tail in scene graph generation. IJCAI 2020.[code] [paper]  
• Tao He, Yuan-Fang Li, Lianli Gao, Dongxiang Zhang, Jingkuan Song. Learning from the scene and borrowing from the rich: Tackling the long tail in scene graph generation. IJCAI 2020.[code] [paper]  
• Jingkuan Song, Tao He, Lainli Gao, Xing Xu, Hengtao Shen. Deep region hashing for efficient large-scale instance search from images. AAAI 2018.[code] [paper]  
• Jingkuan Song, Tao He, Lainli Gao, Xing Xu, Alan Hanjalic, Hengtao Shen. Binary generative adversarial networks for image retrieval. AAAI 2018.[code] [paper]  
• Jingkuan Song, Tao He, Hangbo Fan, Lianli Gao. Deep discrete hashing with self-supervised pairwise labels. ECML 2017.[code] [paper]  

Acadamic Service

• As a reviewer for confereces: CVPR, ECCV, ICCV, CVPR, AAAI, ACMMM, CIKM
• As a reviewer for journals: FGCS, JVIS, IJIS, JVCIR