3 accepted papers
Domain adaptive object detection (DAOD) aims to generalize detectors trained on an annotated source domain to an unlabelled target domain. As the visual-language models (VLMs) can provide essential general knowledge on unseen images, freezing the visual encoder and inserting a domain-agnostic adapte…
Tensor program optimization (TPO) based on pre-trained models can effectively reduce the computing time of deep neural networks. However, training of such models is prohibitively expensive, which highly depends on a large-scale dataset and thus requires tremendous time-consuming performance measurem…
GPUs have become the dominant computing platforms for many applications, while programming GPUs with the widely-used CUDA parallel programming model is difficult. As sequential C code is relatively easy to obtain either from legacy repositories or by manual implementation, automatically translating…