7 citations · 9 across the 4 of their papers we have counts for
4 papers
Explaining a machine learning decision to physicians via counterfactuals
Supriya Nagesh, Nina Mishra, Yonatan Naamad +3
Machine learning models perform well on several healthcare tasks and can help reduce the burden on the healthcare system. However, the lack of explainability is a major roadblock t…
ShapeClipper: Scalable 3D Shape Learning from Single-View Images via Geometric and CLIP-based Consistency
Zixuan Huang, Varun Jampani, Anh Thai +3
We present ShapeClipper, a novel method that reconstructs 3D object shapes from real-world single-view RGB images. Instead of relying on laborious 3D, multi-view or camera pose ann…
No RL, No Simulation: Learning to Navigate without Navigating
Meera Hahn, Devendra Chaplot, Shubham Tulsiani +3
Most prior methods for learning navigation policies require access to simulation environments, as they need online policy interaction and rely on ground-truth maps for rewards. How…
The Secrets of Salient Object Segmentation
Yin Li, Xiaodi Hou, Christof Koch +2
In this paper we provide an extensive evaluation of fixation prediction and salient object segmentation algorithms as well as statistics of major datasets. Our analysis identifies…