32 citations · 33 across the 6 of their papers we have counts for
4 papers · 1 filter
LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-training
Silky Singh, Shripad Deshmukh, Mausoom Sarkar +1
Learning object segmentation in image and video datasets without human supervision is a challenging problem. Humans easily identify moving salient objects in videos using the gesta…
Counterfactual Explanation Policies in RL
Shripad V. Deshmukh, Srivatsan R, Supriti Vijay +2
As Reinforcement Learning (RL) agents are increasingly employed in diverse decision-making problems using reward preferences, it becomes important to ensure that policies learned b…
FODVid: Flow-guided Object Discovery in Videos
Silky Singh, Shripad Deshmukh, Mausoom Sarkar +3
Segmentation of objects in a video is challenging due to the nuances such as motion blurring, parallax, occlusions, changes in illumination, etc. Instead of addressing these nuance…
Explaining RL Decisions with Trajectories
Shripad Vilasrao Deshmukh, Arpan Dasgupta, Balaji Krishnamurthy +4
Explanation is a key component for the adoption of reinforcement learning (RL) in many real-world decision-making problems. In the literature, the explanation is often provided by…