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Task Switching Network for Multi-task Learning
(2021)2021 IEEE/CVF International Conference on Computer Vision (ICCV)We introduce Task Switching Networks (TSNs), a task-conditioned architecture with a single unified encoder/decoder for efficient multi-task learning. Multiple tasks are performed by switching between them, performing one task at a time. TSNs have a constant number of parameters irrespective of the number of tasks. This scalable yet conceptually simple approach circumvents the overhead and intricacy of task-specific network components in ...Conference Paper -
CompositeTasking: Understanding Images by Spatial Composition of Tasks
(2021)2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)We define the concept of CompositeTasking as the fusion of multiple, spatially distributed tasks, for various aspects of image understanding. Learning to perform spatially distributed tasks is motivated by the frequent availability of only sparse labels across tasks, and the desire for a compact multi-tasking network. To facilitate CompositeTasking, we introduce a novel task conditioning model – a single encoder-decoder network that ...Conference Paper