1 code implementation • 25 Feb 2024 • Sahal Shaji Mullappilly, Abhishek Singh Gehlot, Rao Muhammad Anwer, Fahad Shahbaz Khan, Hisham Cholakkal
We demonstrate the effectiveness of our SS-OWOD problem setting and approach for remote sensing object detection, proposing carefully curated splits and baseline performance evaluations.
2 code implementations • 11 May 2022 • Gokul Karthik Kumar, Sahal Shaji Mullappilly, Abhishek Singh Gehlot
However, the CNN feature maps still maintain the spatial relationship and we utilize this property to design self-supervised learning approaches to train the encoder of object detection transformers in pretraining and multi-task learning settings.
1 code implementation • DravidianLangTech (ACL) 2022 • Gokul Karthik Kumar, Abhishek Singh Gehlot, Sahal Shaji Mullappilly, Karthik Nandakumar
These models are pre-trained in a self-supervised fashion with a large English text corpus and further fine-tuned with a massive English QA dataset (e. g., SQuAD).