Learning Online for Unified Segmentation and Tracking Models. - Tianyu Zhu 001; Mehrtash Harandi; Rongkai Ma; Tom Drummond (IJCNN, 2021)

Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers. - Tianyu Zhu 001; Markus Hiller; Mahsa Ehsanpour; Rongkai Ma; Tom Drummond; Hamid Rezatofighi (CoRR, 2021)

Learning Instance and Task-Aware Dynamic Kernels for Few Shot Learning. - Rongkai Ma; Pengfei Fang; Gil Avraham; Yan Zuo; Tom Drummond; Mehrtash Harandi (CoRR, 2021)

Adaptive Poincaré Point to Set Distance for Few-Shot Classification. - Rongkai Ma; Pengfei Fang; Tom Drummond; Mehrtash Harandi (AAAI, 2022)

Learning Instance and Task-Aware Dynamic Kernels for Few-Shot Learning. - Rongkai Ma; Pengfei Fang; Gil Avraham; Yan Zuo; Tianyu Zhu 001; Tom Drummond; Mehrtash Harandi (ECCV (20), 2022)

Rethinking Generalization in Few-Shot Classification. - Markus Hiller; Rongkai Ma; Mehrtash Harandi; Tom Drummond (NeurIPS, 2022)

Learning Adaptively with Few Observations and its Applications in Computer Vision. - Rongkai Ma (2022)

Looking Beyond Two Frames: End-to-End Multi-Object Tracking Using Spatial and Temporal Transformers. - Tianyu Zhu 001; Markus Hiller; Mahsa Ehsanpour; Rongkai Ma; Tom Drummond; Ian D. Reid 001; Hamid Rezatofighi (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Divide and Conquer: Rethinking the Training Paradigm of Neural Radiance Fields. - Rongkai Ma; Léo Lebrat; Rodrigo Santa Cruz; Gil Avraham; Yan Zuo; Clinton Fookes; Olivier Salvado (CoRR, 2024)