no code implementations • 15 Apr 2024 • Zhongrui Gui, Shuyang Sun, Runjia Li, Jianhao Yuan, Zhaochong An, Karsten Roth, Ameya Prabhu, Philip Torr
Rapid advancements in continual segmentation have yet to bridge the gap of scaling to large continually expanding vocabularies under compute-constrained scenarios.
no code implementations • 12 Dec 2023 • Shuyang Sun, Runjia Li, Philip Torr, Xiuye Gu, Siyang Li
Existing open-vocabulary image segmentation methods require a fine-tuning step on mask labels and/or image-text datasets.
no code implementations • ICCV 2023 • Runjia Li, Shuyang Sun, Mohamed Elhoseiny, Philip Torr
Hence, humour generation and understanding can serve as a new task for evaluating the ability of deep-learning methods to process abstract and subjective information.
no code implementations • 29 Nov 2022 • Runjia Li, Yang Yu, Charlie Haywood
In this paper, we address the problem of blind deblurring with high efficiency.
no code implementations • 27 Nov 2022 • Ehsan Imani, Guojun Zhang, Runjia Li, Jun Luo, Pascal Poupart, Philip H. S. Torr, Yangchen Pan
Recent work has highlighted the label alignment property (LAP) in supervised learning, where the vector of all labels in the dataset is mostly in the span of the top few singular vectors of the data matrix.