no code implementations • 18 Apr 2024 • Sai Sree Harsha, Ambareesh Revanur, Dhwanit Agarwal, Shradha Agrawal
Our approach handles edits with target objects of varying shapes and sizes while maintaining the temporal consistency of the edit using our novel target and shape aware InvEdit masks.
no code implementations • 6 Apr 2022 • Tejan Karmali, Abhinav Atrishi, Sai Sree Harsha, Susmit Agrawal, Varun Jampani, R. Venkatesh Babu
Existing works in self-supervised landmark detection are based on learning dense (pixel-level) feature representations from an image, which are further used to learn landmarks in a semi-supervised manner.
no code implementations • 1 Jan 2021 • Sai Sree Harsha, Deepak Mishra
Our proposed methods have the ability to handle variable number of nodes in different graphs, and are also invariant to the isomorphic structures of graphs.